Citation
Mouse brain glucocorticoid receptors

Material Information

Title:
Mouse brain glucocorticoid receptors
Added title page title:
Glucocorticoid receptors
Creator:
Gray, Harry E., 1943-
Publication Date:
Language:
English
Physical Description:
vii, 320 leaves : ill. ; 29 cm.

Subjects

Subjects / Keywords:
Binding sites ( jstor )
Corticosterone ( jstor )
Cytosol ( jstor )
Glucocorticoid receptors ( jstor )
Glucocorticoids ( jstor )
Ligands ( jstor )
Plasmas ( jstor )
Rats ( jstor )
Receptors ( jstor )
Steroids ( jstor )
Dissertations, Academic -- Neuroscience -- UF ( mesh )
Glucocorticoids ( mesh )
Neuroscience thesis Ph.D ( mesh )
Genre:
bibliography ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (Ph.D.)--University of Florida.
Bibliography:
Bibliography: leaves 299-318.
General Note:
Photocopy of typescript.
General Note:
Vita.
Statement of Responsibility:
by Harry E. Gray.

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Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
028969985 ( ALEPH )
09301067 ( OCLC )
ABY0595 ( NOTIS )

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Full Text











MOUSE BRAIN GLUCOCORTICOID RECEPTORS


BY


HARRY E. GRAY






















A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


1982




MOUSE BRAIN GLUCOCORTICOID RECEPTORS
BY
HARRY E. GRAY
A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA


This dissertation is dedicated to the memory of
Clarence Phillips Connell


ACKNOWLEDGMENTS
I gratefully acknowledge the interest and support of my supervisory
committee: Drs. William G. Luttge, Robert J. Cohen, Adrian J. Dunn,
John B. Munson, and Don W. Walker.
I would also like to thank Elizabeth Webster and Dr. Neal Kramarcy
for assistance with the steroid radioimmunoassay, Dr. Richard Bonsall
for a particularly concise derivation of the solution to the rate
equation, Charles Densmore for assistance with animal surgery, and Nancy
Gildersleeve for assistance with computer programming and with a number
of biochemical techniques.
iii


TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS iii
ABSTRACT vi
CHAPTER
I.GENERAL INTRODUCTION 1
Biosynthesis, Secretion, and Metabolic
Effects of Glucocorticoids 1
Regulation of Glucocorticoid Secretion 5
Overview of Corticosteroid Mechanisms 9
Anatomical Distribution of Corticosteroid Binding .... 17
Characterization of Soluble Corticosteroid Receptors
in Brain 21
Physiological Regulation of Corticosteroid Receptors . 27
Corticosterone "Membrane Effects" and Receptors 32
Summary 36
II.METHODS FOR THE DETERMINATION OF ASSOCIATION AND
DISSOCIATION RATE CONSTANTS AND FOR THE ESTIMATION OF
TIMES REQUIRED FOR THE ATTAINMENT OF ARBITRARY DEGREES
OF APPROACH TO EQUILIBRIUM BY NON-COOPERATIVE, SINGLE
SITE LIGAND-RECEPTOR SYSTEMS 39
Introduction 39
Theory 40
Applications and Discussion 44
III.LINEARIZATION OF THE TWO LIGAND-SINGLE BINDING SITE
SCATCHARD PLOT AND "ED" COMPETITION DISPLACEMENT
PLOT: APPLICATION TO THE SIMPLIFIED GRAPHICAL
DETERMINATION OF EQUILIBRIUM CONSTANTS 55
Introduction 55
Theory and Application 57
Discussion 84
iv


Page
IV.EQUILIBRIUM BINDING CHARACTERISTICS AND HYDRODYNAMIC
PARAMETERS OF MOUSE BRAIN GLUCOCORTICOID BINDING SITES ... 86
Introduction 86
Materials and Methods 88
Results 109
Discussion 205
V.THE BINDING OF CORTICOSTERONE TO A CBG-LIKE COMPONENT
OF MOUSE BRAIN CYTOSOL 219
Introduction 219
Materials and Methods 225
Results 232
Discussion 257
VI.KINETIC STUDIES OF MOUSE BRAIN GLUCOCORTICOID
RECEPTORS 261
Introduction 261
Materials and Methods 264
Results 271
Discussion 292
VII.GENERAL DISCUSSION 297
BIBLIOGRAPHY 299
BIOGRAPHICAL SKETCH 319
v


Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
MOUSE BRAIN GLUCOCORTICOID RECEPTORS
By
Harry E. Gray
December 1982
Chairman: William G. Luttge
Major Department: Neuroscience
Glucocorticoid binding sites in cytosol prepared from whole brains
of female CD-I mice perfused 3-5 days after ovariectomy-adrenalectomy
were studied by equilibrium, kinetic and transport methods. In the
standard buffer (containing 10 mM Na^MoO^ and 2 mM dithiothreitol, DTT)
both unoccupied and occupied binding sites for [ Hjdexamethasone (DEX)
were stable at 2C. The absence of DTT resulted in rapid loss of
unoccupied sites, and the absence of molybdate resulted in loss of
unoccupied sites with a t^ of 1 h at 12C and 10 h at 2C.
Equilibrium isotherms revealed one apparent class of saturable,
3 3
high-affinity binding sites (each) for [ H]DEX, [ Hjtriamcinolone
3
acetonide (TA), and [ Hjcorticosterone (B), but the concentration of
3 3
sites for [ H]DEX and [ H]TA (putative receptors) was only 63% of the
3
complete ensemble of [ H]B sites. The concentration of DEX-displaceable
3
[ H]B sites was equivalent to the receptor concentration measured with
vi


[3H]DEX and [3H]TA. DEX failed to interact with 37% of the [3H]B sites;
these sites resembled corticosterone binding globulin (CBG). The
(decreasing) order of steroid affinity for the putative receptors
measured with the [3H]1igands was: L3H]TA > [3H]DEX > [3H]B. The
competing steroids that were tested fell into the following order of
decreasing affinity (increasing Kdi) for the [ H]dexamethasone binding
sites: DEX > B > 11-deoxycorticosterone > progesterone % cortisol >
aldosterone > cortexolone > testosterone.
3 3
Measured rate constants for the association of [ H]DEX, [ H]TA, and
3
[ H]B with the receptors were very similar. The very different
affinities of these agonist ligands resulted from their quite different
dissociation rate constants. Progesterone at concentrations greater
than lCT^ M (but not DEX itself) significantly accelerated dissociation
3
of the L H]DEX-receptor complexes.
3
Nonactivated [ H]TA-receptor complexes possessed Stokes radius
o
77 A, sedimentation coefficient 9.7 S, and molecular weight 315,000
3
dal tons; heat-activated [ H]TA-receptor complexes (confirmed by
O
DNA-cellulose binding) possessed Stokes radius 58 A, sedimentation
coefficient 3.7 S, and molecular weight 90,000 daltons. Physical
o
characteristics of the cytosol CBG-like binder (Stokes radius 46 A,
sedimentation coefficient 4.1 S, molecular weight 70,000 daltons) were
indistinguishable from those of plasma CBG.
VI 1


CHAPTER I
GENERAL INTRODUCTION
Biosynthesis, Secretion, and Metabolic
Effects of Glucocorticoids
The adrenal cortex produces over forty steroids, but only a few of
these are secreted in biologically significant quantities. The major
active secretions are classified as glucocorticoids (e.g., cortisol,
corticosterone, 11-deoxycortisol) or mineralocorticoids (e.g.,
aldosterone, deoxycorticosterone), with 21 carbon atoms, and weak
androgens (e.g., dehydroepiandrosterone), with 19 carbon atoms (see
Table 1-1). Minor amounts of progestational and estrogenic steriods are
also secreted. The predominant glucocorticoid is cortisol in some
species, e.g., hamster, sheep, and primates, but it is corticosterone in
others, e.g., rat, mouse, and rabbit (Seth, 1969). Although cortisol is
the predominant circulating glucocorticoid in primates, corticosterone
may comprise a significant or even major fraction of the glucocorticoid
bound in brain cell nuclei (Turner, Smith and Carroll, 1979).
The enzymatic pathways for the synthesis of adrenal steroids from
cholesterol, which the adrenals may take up from blood or synthesize
from acetate, are well known (e.g., Fregly and Luttge, 1982). Briefly,
cholesterol undergoes a series of hydroxylations, catalyzed by the mito
chondrial desmol ase enzyme complex, leading to pregnenolone, which is
then converted to progesterone by the actions of the microsomal enzymes
1


Table 1-1: Adrenal steroid hormone names and abbreviations
IUPAC Names
Abbreviations
4-Androsten-17g-ol-3-one
5-Androsten-3g-ol -17-one
4-Pregnen-3, 20-dione
4-Pregnen-lla, 17a, 21-triol-3, 20-dione
4-Pregnen-llB, 17a, 21-triol-3,20-dione
4-Pregnen-l1e,21-diol-3,20-dione
4-Pregnen-l1b,21-diol-3,18,20-trione
4-Pregnen-l7a-ol-3,20-dione
4-Pregnen-l7a,21-diol-3,20-dione
4-Pregnen-21-ol-3,20-dione
5-Pregnen-3B-ol-20-one
1.4-Pregnadien-9-fluoro-llB,16a,17a,
21-tetrol-3,20-dione 16, 17-acetonide
1.4-Pregnadien-9-fluoro-16a-methyl-11B,
17a,21-triol-3,20-dione
T
DHEA
P4
lla-F
F
B
Aldo
17a-0H-P4
DOF, S
DOC, 11-DOC
Pg
TA
DEX
Trivial Names
Testosterone
Dehydroepiandrosterone
Progesterone
Epicortisol
Cortisol
Corticosterone
Aldosterone
17a-Hydroxyprogesterone
Cortexolone
Desoxycorticosterone
Pregnenolone
Triamcinolone Acetonide
Dexamethasone


3B-hydroxy steroid dehydrogenase and 3-ketosteroid isomerase. Some
progesterone is converted to 17a-0H-progesterone by the cytoplasmic 17
a-hydroxylase. Progesterone and 17a-0H-progesterone are converted by a
cytoplasmic C-21 hydroxylase to 11-deoxycorticosterone and 11-deoxy-
cortisol, respectively. A mitochondrial lie- hydroxylase enzyme finally
converts 11-deoxycorticosterone and 11-deoxycortisol to the finished
glucocorticoid products corticosterone and cortisol. The adrenal cortex
does not store its secretions, but it does store an abundance of the
precursor cholesterol in lipid droplets. The adrenal stimulators
adrenocorticotropic hormone (ACTH) and angiotensin II, by processes
involving cyclic AMP, accelerate the conversion of cholesterol to
pregnenolone, the rate-limiting step in adrenal steroidogenesis. This
conversion is rapidly followed by the synthesis and secretion into the
circulation of the active corticosteroids.
Glucocorticoids are so named for their role in regulating glucose
metabolism. They act directly on most tissues, and indirectly influence
all tissues. An early effect of glucocorticoids is the inhibition of
glucose uptake by adipose tissue, skin, fibroblasts, and lymphoid
tissue. There is a decrease in macromolecular (protein, lipid, and
nucleic acid) synthesis and an increase in protein degradation in these
tissues and in muscle. There is an increase in lipolysis in fat cells,
and a depletion of glycogen in muscle. These catabolic actions result
in the release of amino acids, free fatty acids, glycerol, and
nucleotides into the circulation. In contrast, the actions of
glucocorticoids in the liver are primarily anabolic, resulting in a
general increase in RNA and protein synthesis, as well as the specific


4
induction of a number of enzymes. The amino acids derived from
peripheral catabclism are substrates for increased glucose formation
(gluconeogenesis) in liver, and to a lesser extent in the kidney.
Glycogen accumulates in liver, and blood glucose levels tend to rise.
The latter change induces a compensatory increase in insulin, which
counteracts many of the glucocorticoid effects.
Certain tissues are spared from the catabolic actions of
glucocorticoids brain, red blood cells, heart, liver, kidney. These
tissues, perhaps more essential than others, may rather enjoy the
additional circulating glucose diverted from elsewhere or produced by
gluconeogenesis. The diverse actions of glucocorticoids may thus make
teleological sense as a coordinated mechanism for making glucose
maximally available to certain essential tissues during and immediately
following periods of environmental challenge or stress.
Glucocorticoids also have many diverse effects not related to
glucose metabolism. They act at multiple sites to suppress inflammatory
and allergic reactions, including inhibition of extravasation and
migration of leucocytes, edema, and phagocytosis, decrease in the
circulating lymphocytes and eosinophils, involution of the thymus, lymph
nodes and spleen, and decrease in antibody production. The lungs
respond to glucocorticoids with enhanced catecholamine sensitivity,
bronchodilation, and decreased vascular resistance. There may be
anabolic effects in the development of some organs, for example the
induction of surfactant secretion in the fetal lung. Glucocorticoid
actions have been reviewed comprehensively by Baxter and Rousseau
(1979). The effects of corticosteroids on the nervous system and


5
behavior have also been reviewed recently (Bohus, de Kloet and Veldhuis,
1982; Rees and Gray, 1983).
Regulation of Glucocorticoid Secretion
Glucocorticoids are released from the adrenals in response to ACTH,
which is in turn secreted by cells of the anterior pituitary in response
to corticotropin releasing hormone (CRH), of hypothalamic and perhaps
extrahypothalamic origin (Sayers and Portanova, 1975; Vale, Spiess,
Rivier and Rivier, 1981). Three factors are known to control
glucocorticoid secretion: stress, rhythms, and corticosteroid feedback.
The pituitary-adrenal system responds within a few minutes to a
wide variety of noxious stimuli, termed stressors. The "general
adaptation syndrome" (Selye, 1950) produced by this pituitary-adrenal
stress response is both nonspecific with respect to a variety of stimuli
and relatively slow to develop, in contrast to the autonomic responses
which can produce relatively stimulus-specific and extremely rapid
adaptive changes in many organ systems. Although a distinction is
frequently drawn between "physiological" stressors (e.g., trauma,
hemorrhage, hypoxia, infection, ether, cold, heat, fasting), and less
noxious "psychological" stressors (e.g., immobilization, handling, mild
electric shock, loud noise, and situations that produce fear, guilt,
anxiety, or frustration), this distinction is often blurred in practice.
When pain, discomfort, and emotional reactions were avoided carefully,
several "physiological stressors" (fasting, heat, exercise) no longer
elevated corticosteroid levels. This finding led Mason (1971) to
suggest that the essential property of all stressors may be the ability
to elicit a behavioral response of emotional arousal or hyperalerting,


6
which prepares the organism for flight, struggle, or strenuous exertion
in a threatening situation.
The circadian rhythm in glucocorticoid secretion appears to be
entrained by the organism's rest-activity cycle. The secretory peak
occurs just before the active phase, even when the relation of activity
to the lighting cycle is reversed, as in humans working on night shifts,
or in rats fed only during the day (e.g., Morimoto, Arisue and Yamamura,
1977). In addition to the circadian rhythm, higher frequency
oscillations in corticosteroid secretion have been revealed by frequent
sampling (every 20 minutes). Recent evidence (Holaday, Martinez and
Natelson, 1977) has shown that this pulsatile secretion, previously
regarded as "episodic," actually follows an ultradian rhythm (frequency
greater than one cycle in 24 hours), having a predominant periodicity of
about 90 minutes and other components harmonically related to the
circadian rhythm. These rhythmic fluctuations in plasma cortisol were
synchronized among 8 isolated, restrained, undisturbed monkeys,
indicating their entrainment by environmental factors such as the
feeding or lighting schedule. The unexpected finding that ultradian
cortisol rhythms were not disrupted by infusion of supramaximal ACTH
challenges the classic concept that periodic bursts of corticosteroid
output depend entirely on the immediately preceding release of ACTH.
The physiological function of corticosteroid rhythms is unknown.
ACTH secretion is regulated by two temporally distinct negative
feedback mechanisms, a rate-sensitive fast feedback (FFB), which occurs
5 to 30 minutes after steroid administration, and a proportional,
delayed feedback (DFB), which appears after one or more hours (Dallman
and Yates, 1969; Jones, Hillhouse and Burden, 1977). These two phases


7
are separated by a "silent" period, during which negative feedback is
not observed. Differences in the steroid structure-activity
relationships for FFB and DFB indicate that different receptor
mechanisms may be involved.
There is evidence that corticosteroid feedback actions may be
exerted at multiple sites. The sensitivity of ACTH-secreting pituitary
cells to inhibition by physiological doses of natural and synthetic
corticosteroids has been established clearly by studies in which the
possibility of hypothalamic involvement was circumvented and by studies
of pituitary cells in vitro (Kendall, 1971; Jones et al., 1977).
Hypothalamic tissue in vitro also showed a FFB effect of corticosterone,
due to decreased release of CRH (Jones et al., 1977). A series of
studies (e.g., Feldman and Conforti, 1980) demonstrated that posterior
hypothalamic deafferentation, dorsal fornix section, or dorsal hippo
campectomy reduced the inhibitory DFB effect of the synthetic
fluorinated glucocorticoid, dexamethasone on both basal and ether
stress-induced corticosterone secretion in the rat. These findings
suggest that the dorsal hippocampus also participates in the feedback
regulation of pituitary-adrenal function. Furthermore, several studies
(e.g., Carsia and Malamed, 1979) have indicated a direct inhibitory
effect of corticosterone and cortisol on ACTH-induced corticoster-
oidogenesis, suggesting that the self-suppression of adrenocortical
cells by end products may provide an additional fine adjustment of
steroidogenesis. What remains to be determined is the relative
physiological importance of glucocorticoid feedback at the various
sites--anterior pituitary, hypothalamus, extrahypothalamic structures,
and the adrenal cortex itself. Although it appears that dexamethasone


8
may act primarily at the pituitary level (Sakakura, Yoshioka, Kobayashi
and Takebe, 1981), the pituitary may be less responsive to natural
glucocorticoids. One explanation for this difference is that anterior
pituitary cytosol contains a transcortin-1ike macromolecule, which like
plasma transcortin binds corticosterone but not dexamethasone and has
negligible affinity for DNA-associated acceptor sites in the nucleus
(Koch, Lutz, Briaud and Mialhe, 1976). Thus, while the transcortin-1ike
binders cannot interfere with the action of dexamethasone, they can, by
competing with the "true" cytoplasmic glucocorticoid receptors, reduce
the amount of corticosterone able to interact with these receptors.
Such a mechanism might insure that under non-stress conditions the
pituitary glucocorticoid receptors would not be occupied, thus allowing
them to function only in response to much higher, stress-induced levels
of corticosterone.
Glucocorticoids may also act directly upon the hypothalamus and
pituitary to modulate the production or secretion of hormones other than
CRH and ACTH, such as TRH, TSH, and GH (e.g., Burger and Patel, 1977).
The "compensatory" hypertrophy of the remaining adrenal following
unilateral adrenalectomy was long considered a result of decreased
corticosteroid feedback. However, compensatory adrenal growth was
recently shown to be neurally rather than hormonally mediated, dependent
on reciprocal neural connections between the hypothalamus and adrenal
(Dallman, Engeland and Shinsako, 1976).
While much progress has been made in elucidating individual factors
influencing pituitary-adrenal activity (neural input, feedback, stress,
rhythms), there is still a significant gap in our understanding of how
these isolated components function together in the intact organism.


9
Overview of Corticosteroid Mechanisms
Many of the effects of corticosteroids are believed to be mediated
by interactions of the steroid molecules with steroid-specific
cytoplasmic macromolecular receptors which concentrate as hormone-
receptor complexes in the target cell nuclei, where they initiate the
alterations in specific RNA and protein metabolism that then lead to the
ultimate physiological, neuroendocrine and behavioral effects. Other
less well-understood steroid effects may result from direct interactions
of the steroid molecule with components of target cell membranes. Some
established and hypothetical events in corticosteroid action are
represented in Fig. 1-1.
Although the natural adrenal steroids are soluble enough to be
transported unassisted in plasma, about 75% of the circulating
glucocorticoid (cortisol or corticosterone) is bound to an a-globulin
called transcortin or corticosteroid-binding globulin (CBG), about 15%
is bound to serum albumin, and only about 10% is free (Westphal, 1975).
Plasma transcortin does not seem to be necessary in any way for the
biological activity of the steroids; current evidence supports the dogma
that only the free steroid in the plasma can exert physiological action.
Although the brain capillary transit time is too short in relation to
the dissociation rate or half-life (t^) of the CBG-glucocorticoid
complex to allow the uptake of CBG-bound cortisol and corticosterone,
the albumin-bound corticosteroids dissociate rapidly enough to be
available for transport through the blood-brain barrier (Pardridge,
1981). (Liver capillary transit time and membrane permeability are


Fig. 1-1. Some established and hypothetical steps in corticosteriod action. S =
molecule, R = receptor, APO-R = aporeceptor.
Different shapes of R represent different conformations or covalent modifications
broken lines indicate hypothetical mechanisms or loci of hormone action.
steroid
The


ACIDS TRANSMITTERS ETC.


12
greater, allowing uptake of both albumin and CBG-bound glucocorticoids.)
Transcortin does reduce the amplitude of free glucocorticoid variations
in response to large rhythmic or stress-induced changes in adrenal
output. The potent synthetic fluorinated glucocorticoids (dexamethasone
and triamcinolone), as well as the natural mineralocorticoid
aldosterone, are only very weakly bound by transcortin. Since the
natural glucocorticoids can significantly occupy mineralocorticoid
receptors when present in high concentrations, and since the total
concentration of plasma glucocorticoids is much greater than the normal
concentration of aldosterone, the "buffering" effect of glucocorticoid
binding by transcortin is apparently necessary to prevent the saturation
of mineralocorticoid receptors by glucocorticoids (Funder, Feldman and
Edelman 1973). It is not known why the glucocorticoid/mineralocorticoid
ratio is so large, requiring this rather peculiar mechanism to confer
specificity of hormone action.
It is often assumed that target cell membranes do not present a
barrier to free lipophilic steroids, and that their passage into the
target cell is governed solely by simple diffusion. Recent studies
have, however, demonstrated for at least several different cell types
(isolated rat liver and pituitary cells and ACTH-secreting mouse
pituitary tumor cells) that glucocorticoid passage through the plasma
membrane may involve carrier-mediated transport in addition to simple
diffusion (e.g., Harrison, Fairfield and Orth, 1977; Koch, Sakly and
Lutz-Bucher, 1981). It is not yet clear how general this phenomenon may
be in terms of other target cells and hormones.


13
It has been observed that some steroids may have several different
actions in the nervous system that are mediated independently by their
different metabolites, but there is no evidence that the metabolites of
the natural glucocorticoids corticosterone and cortisol are functionally
important and possess their own non-enzymatic high-affinity binding
sites in brain or pituitary. Following in vivo injections of
[ Hjcorticosterone the radioactivity extracted with methylene chloride
from the nuclear fraction of rat brain was found to consist of
approximately 90% authentic (isochromatographic) corticosterone (McEwen,
Magnus and Wallach, 1972). Further investigation of glucocorticoid
metabolism in brain tissue is required, however, since acid metabolites
of cortisol possessing different, specific biological activities (as
enzyme inducers) have recently been found in rat liver (Voigt and
Sekeris, 1980).
The cytoplasmic steroid receptors are thermolabile proteins with
stereo-specific binding sites. Before the steroid can bind to the
-9
receptor with high affinity (K^ 10 M), the corticosteroid receptor
protein ("aporeceptor") may be required to undergo an energy-
dependent transformation (possibly a phosphorylation) in order that the
potential binding site may be "switched on" to the appropriate
conformation for interaction with the steroid. A rapid "switching-off"
or down-regulation of the steroid-binding sites (possibly mediated by a
phosphatase) has also been observed, suggesting that cells may utilize
an internal phosphorylation-dephosphorylation feedback cycle to modulate
physiological responses by regulating the amount of receptor capable of
interacting with free steroid. Thus, under many circumstances a
substantial pool of latent or "cryptic" aporeceptors may be present in


14
many target cells. This dynamic regulation of the hormone binding site
itself has only recently been explored in cells derived from a few
peripheral tissues (e.g., Sando, Hammond, Stratford and Pratt, 1979),
and is an intriguing area for brain studies (e.g., Luttge, Densmore and
Gray, 1982). The number of receptors capable of interacting with free
steroid may be subject to additional regulation by certain proteolytic
enzymes that can disconnect the steroid binding site from the region of
the receptor molecule that contains the nuclear binding site, resulting
in non-functional steroid-binding fragments termed "mero-receptors"
(e.g., Niu, Neal, Pierce and Sherman, 1981).
After binding, the non-covalent cytoplasmic steroid-receptor
complex must next undergo a transformation that results in the
development of a high affinity for certain nuclear components associated
with the genome. This process of "activation" probably involves a
steroid-induced conformational change in the acidic receptor protein
which brings a positively-charged "acceptor" binding site to the surface
of the molecule (e.g., Barnett, Schmidt and Litwack, 1980). The nuclear
"acceptors" to which the activated receptor complexes now bind are
unidentified components of chromatin (possibly non-histone proteins)
that possess high-affinity and, to varying extents, tissue- and
receptor-specific binding domains. Although the acceptors are probably
not merely specific DNA nucleotide sequences, they do appear to regulate
the interactions of the steroid-receptor complexes with the DNA (e.g.,
Bugany and Beato, 1977; Cidlowski and Munck, 1980).
Following the formation of the ternary steroid-receptor-acceptor
complex the chromatin structure becomes altered in subtle ways that lead
to changes in the rates of transcription of specific mRNA species (e.g.,


15
Johnson, Lan and Baxter, 1979). These specific mRNA molecules are then
translated to produce the proteins that mediate the hormone-induced
physiological responses. Fig. 1-1 indicates that the proteins whose
rates of synthesis are modulated by the steroid may encompass a broad
spectrum of cellular functions: additional steroid receptors;
components or modulators of membrane transport mechanisms; enzymes of
intermediary metabolism; protein kinases, components of peptide hormone-
or neurotransmitter-sensitive receptor-adenylate cyclase complexes, and
other modulators whose altered synthesis may contribute to the so-called
"permissive" effects of steroids; and even specific proteins required
for some catabolic steroid effects (e.g., thymus involution) are all
examples of proteins that may be regulated to produce the ultimate
steroid response (e.g., Baxter and Rousseau, 1979).
After exerting their genomic effect, the receptors are either
degraded or recycled back to their unbound, nonactivated cytoplasmic
form by a process that may be linked to cell metabolism by a requirement
for ATP (e.g., Aronow, 1978). The nuclear "processing" of the
receptors, the "off-reaction," and receptor recycling are understood
very poorly; it is possible that some steroid dissociation may occur
before the receptors are released from their chromatin acceptor sites,
and there are hints that the process may be coupled to the proposed
cyclic transformations of the steroid binding sites. The released
steroid molecules may either re-enter the receptor cycle or diffuse out
of the cell into the circulation to enter another cell or to be
metabolized and excreted.
Fig. 1-1 also indicates several largely unexplored potential
mechanisms of steroid influence on cellular function that do not


16
directly involve events at the genome. The suggestions that
corticosteroid-receptor complexes may directly exert translational
(e.g., Kulkarni, Netrawali, Pradhan and Sreenivasan, 1976) or
post-translational (e.g., Trajkovic, Ribarac-Stepic and Kanazir, 1974)
control over specific protein synthesis or that they may directly
regulate membrane transport mechanisms are hypothetical at present. The
suggestion that some glucocorticoid effects may result from the
interaction of free steroids with intracellular membrane systems is also
hypothetical (for review, see Nelson, 1980); glucocorticoids are known
to modify some membrane properties, but no functional consequences of
such changes are yet well established. Free steroids may also exert
important effects at the cell plasma membrane; these include rapid,
steroid-specific changes in the firing rates of some neurons (for
review, see Feldman, 1981; McEwen, David, Parsons and Pfaff, 1979).
Since a steroid's affinity for the cytoplasmic receptors does not
adequately predict the magnitude of the physiological response, it is
necessary to classify all steroids into one of four categories on the
basis of their physiological effectiveness (Rousseau, Baxter and
Tomkins, 1972). Optimal inducers are steroids that all produce the same
maximal response when present in saturating amounts. For example,
aldosterone will produce as great a glucocorticoid response as
dexamethasone (in many tissues) when present in very high concen
trations. Suboptimal inducers elicit smaller, less-than-maximal
responses even when present in saturating concentrations; 11-deoxy
corticosterone is an example of a suboptimal glucocorticoid. Anti
inducers or antihormones produce no typical physiological responses by
themselves, but rather behave as competitive inhibitors of the active


17
hormones; progesterone and cortexolone (11-deoxycortisol) are
antiglucocorticoids. Finally, inactive steroids do not bind to the
specific steroid receptors at all. It should be stressed that the
classification of a particular steroid must refer to a specific,
measurable response and may vary among species and from one tissue to
another.
It is believed that different ligands can promote different degrees
of conformational change, leading to the formation of steroid-receptor
complexes with different states of "partial activation" (different
affinities for nuclear acceptor components). Munck and Leung (1977)
have proposed that each relevant steroid or class of steroids binds to
the receptor and promotes a subsequent conformational change that
differs in degree from that produced by other steroids. Optimal
inducers produce the highest degrees of activation, and anti-inducers
either do not promote activation or promote minimal, ineffective
increases in affinity for nuclear acceptors. Suboptimal inducers
produce intermediate states of activation. Other models of agonist and
antagonist interactions with the glucocorticoid receptor are also under
active consideration (Rousseau and Baxter, 1979; Sherman 1979).
Anatomical Distribution of Corticosteroid Binding
3
Neuronal nuclear concentration of [ Hjcorticosterone has been
demonstrated by autoradiography in structures of the limbic system,
brain stem, and spinal cord, but not in the hypothalamus (McEwen,
Gerlach and Micco, 1975; Stumpf and Sar, 1975; Warembourg, 1973). In
3
adrenalectomized rats, nuclear accumulation of [ H]corticosterone was
most intense in structures related to the hippocampus, including the


18
postcommissural hippocampus, dentate gyrus, induseum griseum
(supracallosal hippocampus), anterior (precommissural) hippocampus, and
subiculum. Strong nuclear labeling was also seen in the lateral septum,
amygdala (cortical, central, and basomedial nuclei), and the piriform,
entorhinal, suprarhinal, and cingulate cortices. Additional labeling,
although weaker and less frequent, was present in the anterior olfactory
nucleus, medial amygdaloid nucleus, habenula, red nucleus, and
subfornical organ. Motor neurons in cranial nerve nuclei and spinal
cord were strongly labeled, and some glial cells were weakly labeled
(Stumpf and Sar, 1979). The pattern of in vivo uptake of [ H]cor-
ticosterone determined by autoradiography (highest in hippocampus and
septum, followed by amygdala, cortex and hypothalamus) agrees well with
the anatomical distribution of cytoplasmic [ Hjcorticosterone binding
sites (McEwen et al., 1972; Grosser, Stevens and Reed, 1973); and with
3
the patterns of [ H]corticosterone binding found in purified nuclei both
o
following [ Hjhormone injections in vivo (McEwen, Weiss and Schwartz,
1970) and after incubation of brain slices with [ Hjcorticosterone in
vitro (McEwen and Wallach, 1973; de Kloet, Wallach and McEwen, 1975).
Corticosterone target cells have been observed in the anterior pituitary
of the rat (Warembourg, 1973) and Pekin duck (Rhees, Abel and Haack,
1972), but not the rhesus monkey (Pfaff, Gerlach, McEwen, Ferin, Carmel
and Zimmerman, 1976).
3
The distribution of target cells for [ Hjcortisol in the brains of
adrenalectomized rats was identical to that for [ Hjcorticosterone
(Stumpf and Sar, 1973). Nuclear binding sites for cortisol appeared to
be saturated by endogenous corticosteroids in adrenally intact mice
(Schwartz, Tator and Hoffman, 1972) and guinea pigs (Warembourg, 1973).


19
The synthetic glucocorticoid dexamethasone displayed a surprisingly
different pattern of uptake from that of natural glucocorticoids.
Whereas corticosterone and cortisol were concentrated strongly by
neurons, [ H]dexamethasone was accumulated weakly by all types of cells
in the brain (Rees, Stumpf and Sar, 1975; Rhees, Grosser and Stevens,
1975). The labeling was heaviest in epithelial cells of the choroid
plexus and ventricular lumen, and was also observed in vascular
endothelial cells, glia, meninges, ependyma, circumventricular organs,
and in neurons in areas near the third ventricle (preoptic area,
hypothalamus, thalamus) and lateral ventricle (septum, caudate,
amygdala). In contrast to [ Hjcorticosterone, [ Hjdexamethasone was
concentrated only very weakly by hippocampal neurons. Furthermore, the
presence of endogenous adrenal hormones in intact rats did not affect
the pattern of [ Hjdexamethasone localization (Rhees et al., 1975). In
the pituitary, dexamethasone was concentrated heavily by cells in the
pars distal is (particularly corticotrophs) and pars nervosa, but not
pars intermedia (Rees, Stumpf, Sar and Petrusz, 1977). The autoradio
graphic data were consistent with the pattern of in vivo uptake of
3
[ Hjdexamethasone revealed by direct measurements of tissue radio
activity (de Kloet, van der Vies, and de Wied, 1974).
The strikingly different patterns of distribution of these natural
and synthetic glucocorticoids have been interpreted as evidence for the
existence of at least two classes of glucocorticoid receptors differing
in their distribution and steroid specificity. However, some of the
findings may be explained without reference to the concept of receptor
heterogeneity. There are large differences in the permeability of the


20
blood-brain barrier to different steroids (Pardridge and Mietus, 1979).
Dexamethasone appears to enter the brain more slowly than corti
costerone; time course studies showed that maximal binding in hippo
campal cell nuclei occurred one hour after injection of
3 3
[ Hjcorticosterone, but two hours after [ Hjdexamethasone (de Kloet et
3
al., 1975). Similarly, the cellular accumulation of [ Hjdexamethasone
in the hippocampus seen autoradiographically three hours after injection
was not yet evident at 30 minutes (Rees et al., 1975). The greater
blood-brain barrier to dexamethasone may also explain some discrepancies
between the patterns of nuclear binding of glucocorticoids obtained in
vivo and in slices incubated in vitro. Although the in vivo nuclear
binding of [ Hjcorticosterone in hippocampus was more than ten times
that of [ Hjdexamethasone, this difference was dramatically reduced
(corticosterone: dexamethasone ratio of 1.2 1.5) when slices of
hippocampus were incubated with the steroids in vitro (de Kloet et al.,
1975; McEwen, de Kloet and Wallach, 1976). It is possible that the
small but significant remaining differences in nuclear binding observed
in the in vitro slice experiments (i.e. greater binding of corti
costerone in hippocampus and of dexamethasone in hypothalamus and
pituitary) may have resulted from factors other than glucocorticoid
receptor heterogeneity: for example, differences in the rates of
cellular penetration of the two steroids which may persist in the slice
experiments, and differences in the relative abilities of the two
steroids to promote activation and nuclear binding of the steroid-
receptor complexes (e.g., Svec and Harrison, 1979).


21
Characterization of Soluble Corticosteroid
Receptors in Brain
The natural glucocorticoids, corticosterone and cortisol; the
synthetic glucocorticoids triamcinolone acetonide (TA) and
dexamethasone; and the natural mineralocorticoids, aldosterone and
11-deoxycorticosterone (DOC), bind to steroid-specific, saturable brain
cytosol components believed to be the physiological transducer molecules
or "receptors." One goal of receptor research is to identify the
different classes or categories of adrenal steroid action in the brain
and to study individually the receptors mediating these actions. The
categories "glucocorticoid" and "mineralocorticoid" are defined by
distinguishable peripheral physiological effects and steroid specific
ities; this distinction may be meaningful in the nervous system, but it
should not be assumed a priori that brain steroid effects and speci
ficities closely correspond to those of other organ systems.
In comparison with the corticosteroid receptors found in other
tissues, the few reported physicochemical properties of brain receptors
are generally unremarkable. They have been distinguished from those of
transcortin by a number of criteria; unlike transcortin, the brain
cytoplasmic glucocorticoid binding protein was found to bind the
synthetic steroids dexamethasone and TA with high affinity and to
possess sulfhydryl groups whose modification led to the loss of
functional steroid binding sites (e.g., Chytil and Toft, 1972; McEwen
and Wallach, 1973).
The resolution of the different classes of brain corticosteroid
receptors is confusing because it involves two distinct but related
issues: the possible existence of separate binding sites for natural
and synthetic glucocorticoids; and the distinction between


22
glucocorticoid and mineralocorticoid binding sites. The principal
technique for defining distinct binding sites is the in vitro
measurement of steroid specificity in competition experiments. Oddly,
the actual affinities of different competing steroids for brain cytosol
3
[ H]steroid binding sites have seldom been reported. Specificity data
have typically been reported only as a rank ordering of the abilities of
different steroids to compete for the binding of a given [ H]steroid.
Although both natural and synthetic agonists were bound with
similar high affinities by brain cytosol (Chytil and Toft, 1972),
dexamethasone did not reduce the binding of [ H]corticosterone in whole
brain cytosol to the extent that was predicted from its physiological
potency as a peripheral glucocorticoid (Grosser et al., 1973; McEwen and
Wallach, 1973). In most studies, corticosterone and dexamethasone were
3 3
equally effective in competition for [ Hjdexamethasone and [ H]TA
binding (e.g., Chytil and Toft, 1972; Stevens, Reed and Grosser, 1975;
de Kloet and McEwen, 1976).
Comparative measurements of the total cytosol binding capacity for
corticosterone and dexamethasone have been reported. Because a number
of poorly understood variables (such as the composition of the
incubation buffer, the presence or absence of phosphatase inhibitors,
the time elapsed between tissue homogenization and cytosol labeling with
3
[ H]steroid, etc.) have not yet been fully explored or controlled,
published estimates of apparent binding capacity (B_ ) are often in
max
conflict. The discovery by de Kloet et al. (1975) that the spontaneous
3
loss of [ H]dexamethasone binding capacity from unlabeled cytosol was
3
more rapid than the loss of [ H]corticosterone binding sites, stimulated
experiments in which tissues were homogenized in the presence of the


23
3
[ H]steroids. With this alteration in methodology, binding capacities
3 3
for [ H]dexamethasone and [ H]corticosterone in hippocampal cytosol were
found to be equal, and hypothalamic cytosol had an even slightly higher
capacity for [ H]dexamethasone than for [ Hjcorticosterone (e.g., de
Kloet et al., 1975; Turner and McEwen, 1980).
High affinity mineralocorticoid (type I) binding sites, which occur
in significant concentrations principally in the hippocampus and
associated structures, have been studied in rat brain cytosol (Anderson
and Fanestil, 1976; Moguilewsky and Raynaud, 1980). The mineralo
corticoid receptors have high affinity for aldosterone and DOC and,
surprisingly, an almost equally high affinity for progesterone. Since
[ Hjaldosterone, [ H]corticosterone and [ Hjdexamethasone all bind (with
different affinities) to both glucocorticoid and mineralocorticoid brain
receptor sites, it has been most productive to study the binding of
[ Hjaldosterone in the presence of an excess of the "pure" gluco
corticoid R26988 (Moguilewsky and Raynaud, 1980). Although concen
trations of glucocorticoid and mineralocorticoid receptor sites were
comparable in hippocampal cytosol, the concentration of high-affinity
mineralocorticoid binding sites was much lower than the concentration of
glucocorticoid binding sites in whole brain.
Although the discrepancies between in vivo and in vitro (brain
3 3
slice) nuclear binding of [ Hjcorticosterone and [ Hjdexamethasone can
be explained largely without reference to the possible heterogeneity of
unbound glucocorticoid receptors, several observations (such as the
relatively poor ability of dexamethasone to compete for [ Hjcorti
costerone binding sites) have suggested that natural and synthetic
glucocorticoids may bind to somewhat different receptor populations.


24
When cytosol samples were chromatographed on DEAE-cellulose ion-exchange
3 3
columns, complexes formed with [ H]corticosterone and [ Hjdexamethasone
3
were eluted as multiple peaks, and the proportion of bound [ Hjsteroid
in each of the two major peaks differed for the two glucocorticoids (de
Kloet and McEwen, 1976). Although it is unlikely that the two major
peaks of both hippocampal [ Hjdexamethasone and [ Hjcorticosterone
binding merely represent different pools of activated and nonactivated
receptors, it is quite possible that they are distinct proteolytic
fragments (created in vitro) of a single larger intact glucocorticoid
receptor. Affinity chromatography of rat brain cytosol on columns of
immobilized deoxycorticosterone (DOC) hemisuccinate (subsequently eluted
3
with [ Hjcorticosterone) selectively purified one of the two major
3
[ Hjcorticosterone binding peaks resolved by ion exchange chromatography
(de Kloet and Burbach, 1978).
Apparent receptor heterogeneity was also observed in rat brain (and
pituitary) cytosol following isoelectric focussing of labeled samples on
polyacrylamide gels (MacLusky, Turner and McEwen, 1977). In brain
cytosol three major specific [ Hjcorticosterone binding peaks were
resolved; these had isoelectric points (pis) of approximately 6.8, 5.9
and 4.3. When [ Hjdexamethasone was the ligand only two peaks were
found (the peak at pi 4.3 was absent). Furthermore, the relative sizes
of the two remaining peaks were different for the two ligands. Wrange
(1979) has suggested that the apparent receptor heterogeneity observed
by MacLusky et al. (1977) may have resulted from proteolytic artifacts
and that the brain cytosol [ Hjcortiscosterone binding peak at pi 4.3
(reported by the same workers) can probably be attributed to residual
transcortin (CBG) remaining in the tissue following incomplete


25
perfusion. Wrange found only a single peak of radioactivity (at pi 6.1)
when rats were extensively perfused and hippocampal cytosol samples
labeled with either [ Hjcorticosterone or [ Hjdexamethasone were
analyzed. However, it was not possible to conclude that CBG or a class
of CBG-like binding sites was definitely not present, since free steroid
was removed from the samples prior to the relatively long focussing
procedure, which would have both allowed extensive dissociation of
steroid from the CBG and eventually denatured the steroid binding sites
as they entered the region of low pH. Wrange also found that limited
tryptic digestion of hippocampal cytosol labelled with either
[ Hjcorticosterone or [ Hjdexamethasone produced two peaks of bound
radioactivity having pi values of 6.0 and 6.4. These pi values are
close enough to those reported by MacLusky et al. (1977) to suggest that
proteolytic fragments of a single molecule may have been responsible for
the observed heterogeneity. The relative sizes of the two trypsin-
induced peaks were different when [ Hjdexamethasone was substituted for
[ Hjcorticosterone; this situation may have resulted either from the
possession of slightly different trypsin substrate characteristics by
the receptor complexes formed with the different steroids or from
3
different rates of dissociation of [ Hjcorticosterone from the two
trypsin-induced receptor fragments.
The autoradiographic data reviewed above have led to the suggestion
that neurons contain glucocorticoid receptors that preferentially bind
corticosterone and cortisol, whereas glial cells contain glucocorticoid
receptors having higher affinity for dexamethasone and TA (e.g., McEwen
et al., 1979). There is, however, very little evidence to support this
dichotomy. Although dexamethasone is a potent inducer of glycerol-


26
phosphate dehydrogenase (GPDH) in cultured glial tumor cells, and
cytosol prepared from these tumor cells and from optic nerve
oligodendrocytes contains high-affinity [ Hjdexamethasone binding sites,
glial cells also respond to natural glucocorticoids (e.g., Breen,
McGinnis and de Veil is, 1978; Cotman, Scheff and Benardo, 1978).
Furthermore, there is no evidence (e.g., Clayton, Grosser and Stevens,
3
1977) that brain [ Hjdexamethasone binding capacity increases faster
3
than [ Hjcorticosterone binding capacity during the period of rapid
glial growth associated with myelination. Glial tumor cells were found
to contain only one glucocorticoid receptor with a pi of 5.9,
corresponding to the molecular species that bound [ Hjdexamethasone
preferentially in the rat brain (MacLusky, unpublished, cited by McEwen
et al., 1979). This observation cannot, however, be considered strong
evidence for a neuronal-glial receptor dichotomy, since Wrange (1979)
reported a similar isoelectric binding profile containing only a single
radioactive peak in hippocampal cytosol from perfused animals. It is
possible that different concentrations of proteolytic enzymes in the
cytosol samples prepared from brain tissue and from cultured glial cells
could explain the differences between the [ Hjglucocorticoid binding
profiles observed by MacLusky and colleagues in these different
preparations. The demonstration that [ Hjdexamethasone binding sites
disappear from hippocampal cytosol (in the absence of steroid) more
rapidly than [ Hjcorticosterone binding sites (de Kloet et al., 1975)
may result from the gradual alteration of a single initial population of
steroid binding sites by enzymatic processes that are triggered upon
cell disruption and that proceed rapidly in the absence of protective


27
steroid ligands. This apparent differential loss of free binding sites
for [ Hjdexamethasone and [ H]corticosterone may also result, at least
in part, from the presence of a population of relatively more stable CBG
or CBG-like binding sites in the hippocampal cytosol. Clarification of
this complex issue must await the purification and comparison of both
intact unbound receptors and steroid-receptor complexes.
Physiological Regulation of Corticosteroid Receptors
The ontogeny of the capacity of rat brain cytosol to bind both
natural and synthetic glucocorticoids has been studied. Binding of
[ Hjdexamethasone was very low immediately after birth, but it reached
3
the adult level sooner than [ H]corticosterone binding, which was higher
3
than that of [ H]dexamethasone immediately after birth. Adult levels of
3 3
[ H]corticosterone binding were similar to those of [ H]dexamethasone in
both hippocampal and hypothalamic cytosols (Olpe and McEwen, 1976).
Turner (1978) found that the amount of [ Hjcorticosterone bound by
hippocampal nuclei in adrenalectomized rat pups injected with steroid in
vivo was very small in comparison with adult levels. Furthermore, the
nuclear binding of [ Hjcorticosterone by hippocampal pyramidal and
dentate granule cells as determined by autoradiography was correlated
directly with neuronal age; in the neonatal hippocampus the oldest cells
revealed the heaviest labeling, whereas newly arrived cells showed
little nuclear retention of steroid. Thus, although the aporeceptor
proteins may appear much earlier in development, the production of
receptors with functional binding sites and the potential for activation
to the nucleophilic state may occur relatively late in the differ
entiation of these neurons.


28
An age-related decline in corticosterone receptors has been
reported in mouse hippocampus (Finch and Latham, 1974) and in rat
cerebral cortex (Roth, 1974). Evidence suggests that senescent
intracellular biochemical changes rather than cellular losses are
responsible for the decline in cortical receptors (Roth, 1976).
The concentration of intracellular corticosteroid binding sites
rises in response to steroid deprivation. Adrenalectomy caused a
two-stage increase in the nuclear binding of [ H]corticosterone by
hippocampus in vivo and in vitro (McEwen, Wallach and Magnus, 1974) and
increased glucocorticoid cytosol receptor concentrations (Stevens et
al., 1975; Olpe and McEwen, 1976). The apparent receptor content
increased rapidly for the first 2 hours after adrenalectomy and then
remained at a plateau for about 12 hrs; the second, slower increase
began between 12 and 18 hours after adrenalectomy and approached a new
plateau after about 3 days. The first, rapid change, which parallels
the decline in plasma corticosterone, certainly represents the
disappearance of endogenous corticosterone from brain binding sites and
may also reflect the "switching-on" of the steroid binding sites of
receptors. The interesting long-term increase results from either the
synthesis of new receptors on the "switching-on" of previously
unobservable "cryptic" aporeceptors.
Both the concentration of endogenous corticosteroids and the
occupancy of corticosteroid receptors in the brain vary with changes in
plasma steroid levels. Brain glucocorticoid concentrations, which were
intermediate between free and total plasma concentrations and therefore
possibly equal to the plasma glucocorticoid concentration available for
brain uptake (the free + albumin-bound or "BBB-transportable"


29
concentration) (Carroll, Heath, and Jarrett, 1975), were found to
fluctuate in parallel with both basal circadian and stress-induced
changes in the plasma steroid concentrations (Butte, Kakihana and Noble,
1976; Carroll et al., 1975). Furthermore, the diurnal and stress-
induced increases in plasma corticosterone decreased the in vitro
cytosol binding of [ H]corticosterone in all brain regions examined
(Stevens, Reed, Erickson and Grosser, 1973). In most brain regions of
unstressed animals, glucocorticoid receptor occupancy varies between
about 50% at the diurnal trough and approximately 80% at the peak
(Stevens et al., 1973; McEwen et al., 1974; Turner, Smith and Carroll,
1978a,b). In contrast to other brain regions, the preoptic and septal
areas exhibited a high level of receptor occupancy even during the
morning corticosterone minimum, and no increase at the evening peak
(Turner et al., 1978a,b). However, all brain regions showed a circadian
3
variation in the total concentration of cytosol [ H]corticosterone
3
binding sites. Furthermore, the same dose of [ H]corticosterone
injected into adrenalectomized mice produced higher hippocampal steroid
concentrations at different times of the day (Angelucci, Valeri,
Palmery, Patacchioli and Catalani, 1980). The peak brain concentra
tions varied as the normal circadian rhythm, suggesting that a
steroid-independent rhythm of receptor concentration may persist in the
adrenalectomized animals.
An investigation of the temporal relationship between
glucocorticoid nuclear binding and the availability of cytosol binding
sites led to the unexpected finding that there was no net depletion of
total hippocampal cytosol binding capacity as a result of nuclear
translocation 15-60 min after the injection of fully saturating doses of


30
3 3
either [ Hjcorticosterone or [ H]dexamethasone (Turner and McEwen,
1980). The predicted cytosol receptor depletion was based on
hippocampal nuclear uptake measured following the in vivo [ Hjsteroid
3
injections. Cytosol samples from rats injected with [ Hjsteroids were
3
incubated in vitro with additional [ Hjsteroids to determine the maximal
cytosol steroid binding capacity, but no depletion of this total
capacity as a result of nuclear translocation was ever observed. This
3
investigation also revealed that [ Hjcorticosterone injected in vivo
could occupy no more than 40% of the total cytosol binding sites
measured in vitro. These results suggest the existence of a reserve
pool of aporeceptors or "cryptic" receptors which can be rapidly
converted to the form capable of binding steroids. However, it must not
be assumed that these findings are characteristic only of brain tissue;
the same glucocorticoid injection produced large differences in
cytoplasmic receptor depletion among 6 different rat glucocorticoid
target tissues (Ichii, 1981). For example, an injection of
dexamethasone that depleted 75% of heart and muscle cytoplasmic
receptors depleted only 40% of liver and lung receptors and only 10% of
thymic and spleen receptors (brain samples were not included). Much
larger injections were able to fully deplete receptors in all 6 tissues.
Neuropeptide effects on functional steroid receptor concentra-
tions have been observed. The increase in [ Hjcorticosterone binding
capacity of rat hippocampal cytosol observed after hypophysectomy
combined with adrenalectomy was greater than that after adrenalectomy
alone. Both ACTH^ ^ (steroidogenic) and ACTH^ (devoid of
corticotrophic activity) eliminated the additional increase attributed
to hypophysectomy. Furthermore, vasopressin-deficient (Brattleboro


31
strain) rats were found to have abnormally low hippocampal cytosol
3
[ H]corticosterone receptor levels that could be restored by
9 8
physiological doses of vasopressin or des-glycinamide -arg -vasopressin
(a behaviorally potent analog having low antidiuretic activity) (de
Kloet and Veldhuis, 1980; de Kloet, Veldhuis and Bohus, 1980).
Several observations indicate the possibility of a rapid, dynamic
regulation of the availability of brain steroid binding sites.
Hippocampal electrical stimulation resulted in increased in vivo uptake
of [ H]cortisol into hypothalamic cells and an increase in the
proportion of intracellular hormone bound in the nucleus (Stith, Person
and Dana, 1976a). A single injection of reserpine into cats resulted
(at 16 hrs post injection) in a decreased concentration of cytosol
binding sites for [ Hjdexamethasone (Weingarten and Stith, 1978). A
rapid influence of metyrapone (an inhibitor of adrenal 116-hydroxylase)
on the binding of [ H] cortisol in pig hypothalamic slices incubated in
vitro at 37C has also been reported (Stith, Person and Dana, 1976b).
3
The quantity of [ Hjcortisol bound to cytosol components after 30 min
3
was reduced by 50%, and nuclear-bound [ Hjcortisol was inhibited by 70%;
the mechanism of this inhibition is unknown.
Lesions have been used to explore possible influences of
hippocampal afferents and efferents on the concentration of hippocampal
glucocorticoid receptors. Transection of the fimbria bilaterally for a
duration of 6 or 80 days did not affect either the concentration of
3 3
hippocampal [ Hjcorticosterone and [ Hjdexamethasone receptors or the
increase in this concentration observed following adrenalectomy (Olpe
and McEwen, 1976). Furthermore, fimbria transection in 3-day-old rats
did not affect the normal ontogenetic increase in hippocampal binding


32
3 3
sites for [ H]dexamethasone and [ H]corticosterone. In contrast, the
3
concentration of hippocampal [ H]corticosterone receptors was elevated
30 days (but not 10 days) following lesions which included the lateral
septal nuclei and the precommissural fornix; lesions which included the
medial septal and diagonal band nuclei and the main septal projection to
the hippocampus did not alter hippocampal receptor concentrations at
either 10 or 30 days after the lesions (Bohus, Nyakas and de Kloet,
1978; Nyakas, de Kloet and Bohus, 1979). Following unilateral dorsal
3
hippocampectomy the concentration of [ Hjcorticosterone binding sites in
the contralateral hippocampus was increased by 74% and 41%, respec
tively, 10 and 20 days after lesioning (Nyakas, de Kloet, Veldhuis and
Bohus, 1981). Thus, some hippocampal afferents and efferents may
modulate steroid receptor concentrations.
Corticosterone "Membrane Effects" and Receptors
Some corticosteroid effects on the nervous system are not mediated
by the mobile cytoplasmic receptors that affect gene expression; these
effects may derive from the alteration of membrane properties by the
free steroids themselves or may be mediated by specific membrane-
associated receptors. Proposed mechanisms for such effects have
included the stabilization of lysosomal membranes, which could delay the
release of hydrolytic enzymes; alteration of ribosomal attachement to
the endoplasmic reticulum, which could modify protein synthesis; and
alteration of the binding of calcium to intracellular membranes, which
could influence synaptic function (reviewed in Baxter and Rousseau,
1979; Nelson, 1980).


33
Dexamethasone appeared to elevate tyrosine hydroxylase activity in
the superior cervical ganglion of adrenally intact rats by exerting an
excitatory pharmacological influence directly on preganglionic
cholinergic nerve terminals; very large doses of corticosterone were
completely ineffective, and the slowly-developing effect of
dexamethasone was abolished by a cholinergic receptor antagonist (Sze
and Hedrick, 1979). The effects of synthetic glucocorticoids on
cholinergic neurotransmission have been both excitatory and inhibitory.
The excitability of cat somatic motoneurons was increased (Riker, Baker
and Okamoto, 1975), and the contraction of guinea pig ileum in response
to nerve stimulation was decreased (Cheng and Araki, 1978) by the
steroids; in both cases the evidence suggested a direct steroid action
on cholinergic terminals.
Systemic or local injection of glucocorticoids has been observed to
affect the spontaneous activity of neurons in many brain loci (for
review, see Feldman, 1981). Injection of cortisol in intact,
freely-moving rats rapidly increased spontaneous activity of units in
the anterior hypothalamus and mesencephalic reticular formation, and
decreased unit activity in the ventromedial and basal hypothalamus
(Phillips and Dafny, 1971a,b). Spontaneous activity of basal
hypothalamic neurons in completely deafferented hypothalamic islands was
also rapidly decreased following systemic injection of either cortisol
(Feldman and Same, 1970) or dexamethasone in intact rats (Ondo and
Kitay, 1972). Similarly, iontophoretic application of dexamethasone
onto medial basal hypothalamic neurons in intact rats produced an
immediate depression of cell firing (Steiner, Ruf and Akert, 1969).
Mesencephalic neurons also responded to direct application of


34
dexamethasone with a decrease in firing rate (Steiner et al., 1969), in
contrast to the increase in firing rate after systemic injection of
cortisol reported by Phillips and Dafny (1971a,b). The injection of
dexamethasone into the vicinity of the recording electrode rapidly
produced a dramatic decrease in hippocampal multiple unit activity
(Michal, 1974), but none of 500 hippocampal neurons tested were
responsive to iontophoretic application of either cortisol or corti
costerone (Barak, Gutnick and Feldman, 1977). It is not known if some
of these reported electrophysiological effects of corticosteroids are
mediated by specific receptors, but their short latencies suggest that
they are direct membrane effects not mediated by changes in gene
expression.
The membrane effects of glucocorticoids probably also include the
physiologically important fast feedback (FFB) suppression of the release
of CRH by hypothalamic neurons. The addition of corticosterone to the
in vitro incubation medium blocked the release of CRH produced by the
electrical stimulation of sheep hypothalamic synaptosomes (Edwardson and
Bennett, 1974), and there is evidence that the FFB action of corti
costerone, which is unaffected by a number of pharmacologic agents, may
be mediated by a direct stabilizing interaction of the steroid with the
membrane of the CRH-secreting cell, which decreases the flux of calcium
into its terminals (Jones et al., 1977).
3
Glucocorticoids regulate the uptake of [ Hjtryptophan by isolated
brain synaptosomes incubated in vitro with the steroids; corticosterone
and dexamethasone at concentrations above 10~^M elevated the maximal
rate (\L 1 of tryptophan transport by a high affinity synaptosomal
uptake system from mouse brain (e.g., Sze, 1976). This effect contrasts


35
sharply with the reversal by glucocorticoids of the increase in the V
max
of high affinity GABA uptake into rat hippocampal synaptosomes observed
after adrenalectomy (Miller, Chaptal, McEwen and Peck, 1978). The
latter effect required hormone pretreatment in vivo and was not observed
when the synaptosomes were incubated in vitro with glucocorticoids,
suggesting that in this case the steroid action was probably mediated by
the "classical" mobile receptor pathway.
Synaptic plasma membranes prepared from osmotically-shocked rat
brain synaptosomes have been reported to contain specific binding sites
for glucocorticoids (Towle and Sze, 1978). Specific, saturable binding
of [ H]corticosterone by synaptic membranes was greatest in the
hypothalamus, and lower (but approximately equal) levels were found in
hippocampus and cerebral cortex. The affinity of corticosterone for the
binding sites (Kd 2 10~7M) was similar in the three brain regions, and
both corticosterone and synthetic glucocorticoids had similar affinities
for the membrane sites. Soluble cytoplasmic receptors and synaptic
membrane binding sites in brain are characterized by somewhat different
properties of thermal stability and resistance to hydrolytic enzyme
attack, making unlikely the possibility of artifactual contamination of
the membranes by cytoplasmic receptors. Since the affinity of
corticosterone for the membrane binding sites (Towle and Sze, 1978)
agrees well with the concentration-response relation for the in vitro
stimulation of synaptosomal tryptophan uptake by corticosterone (e.g.,
Sze, 1976), it is possible that the membrane binding sites are involved
in the regulation of tryptophan uptake in the brain.


36
Summary
Glucocorticoids have profound metabolic, neuroendocrine, and
behavioral effects in the mammalian brain (e.g., Rees and Gray, 1982).
Although some of the less-well-understood effects may result from direct
interactions of the steroid with components of target cell membranes,
many of the effects are thought to be mediated by interactions of the
hormone molecules with steroid-specific cytoplasmic and nuclear
macromolecular receptors that concentrate as activated hormone-receptor
complexes in the target cell nuclei, where they initiate the changes in
gene expression that produce the ultimate physiological effects. The
objectives of brain corticosteroid receptor research are to improve our
extremely limited understanding of the basic mechanisms of receptor
capacitation, activation, nuclear concentration and recycling; to
examine whether the receptor systems for corticosteroid hormones in
brain (and pituitary) resemble closely those operative in other target
tissues; and to determine how the components of the receptor system are
altered in the clinically relevant conditions (such as experimentally-
induced diabetes, genetically-determined obesity and hypertension, and
normal age-related brain senescence) that are correlated with changes in
receptor function.
The experiments presented in this dissertation have been designed
to examine a number of the specific physicochemical properties of
soluble mouse brain glucocorticoid binding sites. The mouse has been
chosen for this research for several reasons. Although a few published
studies have indicated the existence of receptors in the mouse brain
(e.g., Finch and Latham, 1974; Nelson, Holinka, Latham, Allen and Finch,
1976; Angelucci et al., 1980), no basic characterization of the kinetic


37
and equilibrium binding parameters or the steroid specificity of these
receptors has been reported. Although a modest body of literature
(reviewed above) concerned with the properties of rat brain gluco
corticoid receptors already exists, recent improvements in receptor
methodology have led us to believe that many of the published rat brain
results are probably questionable, and thus that complete reexamination
of the rat brain receptor system must eventually be undertaken.
Therefore, we have chosen the mouse primarily for obvious economic
reasons, and because it is relatively easy to rapidly perfuse and remove
a large number of mouse brains. The decision to use the mouse instead
of the rat has had little impact on the choice or design of specific
experiments.
Since it is necessary to eliminate both endogenous gonadal and
adrenal steroids before killing the animals, females have been used
because they can be simultaneously ovariectomized and adrenalectomized
through the same incisions. We have used whole mouse brain cytosol
because most of the experiments required large amounts of receptor
material and since there is no evidence that there are brain regional
differences in the physicochemical properties of corticosteroid
receptors. Since the use of smaller brain regions would not have
enabled us to distinguish between cell types, it was felt that the
additional expense and effort required to work with a smaller brain
region such as dorsal hippocampus would not be rewarded adequately.
We have used the labeled glucocorticoids [ Hjcorticosterone,
3 3
[ H]dexamethasone and [ H]triamcinolone acetonide (cyclic acetal).
3
[ H] Dexamethasone was used to perform both equilibrium and kinetic
3
studies; [ Hjcorticosterone was employed to examine the possible


38
. O
contribution of transport proteins to the total pool of [ H]corti-
costerone binding sites, whereas the nearly-irreversible ligand
[ H]triamcinolone acetonide was used for the lengthy procedures
examining the size and shape of the receptors. In contrast to many of
the older receptor studies with rat brain reviewed above, our
experiments have used a buffer containing ingredients that prevent loss
of unoccupied binding sites at 0-4C; used a rapid assay that can both
measure association kinetics conveniently and assay rapidly-
dissociating binding complexes; considered the possible consequences of
the failure to allow adequate time for "equilibrium" incubations at low
ligand concentrations; determined steroid specificity by applying
mathematically correct procedures to the analysis of competition data;
explored the contribution of CBG-like binding sites to the total pool of
corticosterone binding sites, and examined binding site sizes and shapes
to assess the homogeneity of the in vitro receptor population. Before
presenting experimental data we discuss (in chapters II and III) some
simple applications of the binding rate equation and propose some
improvements to the methods of graphical analysis of equilibrium
competition data currently in use.


CHAPTER II
METHODS FOR THE DETERMINATION OF ASSOCIATION AND
DISSOCIATION RATE CONSTANTS AND FOR THE ESTIMATION OF TIMES
REQUIRED FOR THE ATTAINMENT OF ARBITRARY DEGREES OF APPROACH
TO EQUILIBRIUM BY NON-COOPERATIVE, SINGLE SITE
LIGAND-RECEPTOR SYSTEMS
Introduction
The rate equation for noncooperative, single site ligand binding
systems may be written
dBL/dt = ka (SL-BL)(B0-BL)-kdBL, (2-1)
where B^ is the concentration of specifically-bound ligand, S^ is the
total ligand concentration, Bq is the total concentration of binding
sites, ka and k^ are the second-order and first-order association and
dissociation rate constants, and t is the time of incubation. The exact
solution to this equation gives the value of B^ as a function of time
for the given incubation conditions if the rate constants (or the
equilibrium dissociation constant, K^, and one of the rate constants)
and the concentration of ligand and binding sites are known (e.g., De
Lean and Rodbard, 1979; Vassent, 1974). Thus, if nonspecific binding
and loss due to the inactivation of binding sites may be neglected as an
approximation, the solution to the rate equation provides an estimate of
the time required for any arbitrary degree of approach to the
equilibrium value of specific binding. As an example of its utility,
39


40
the solution to the rate equation has been used to examine the effect of
inadequate incubation time (during which equilibrium was not attained
under conditions of low ligand concentration) on measured "equilibrium"
dissociation constants (Aranyi, 1979; Yeakley, Balasubramanian and
Harrison, 1980). The solution to the rate equation can also provide
insight into several superficially paradoxical phenomena, such as the
observation that the degree of approach to equilibrium within a given
time is not always a monotonically increasing function of ligand
concentration (Vassent, 1974). We present a concise derivation of a
computationally convenient form of the solution and discuss several of
its applications. Methods for the determination of association and
dissociation rate constants (not requiring the complete solution to the
rate equation) are also discussed.
Theory
Equation (2-1) may be rewritten in the classical Ricatti form as
d6L/dt kaB2-ka(KdL+SL+Bfl)BL+kaSLB0, (2-2)
where k^ has been replaced by At equilibrium dB^/dt=0 and thus
(at equilibrium)
BL (KdL+SL+B0)BL+SLB0 = * (2-3)
This may be rewritten as
(bl-p)(bl-q) = 0,
(2-4)


41
where
P /B
(2-5)
and
Q = (KdL+W[(KdL+SL+B0)2-4 SlB0:1/2)/2. (2-6)
The smaller root, P, gives the value of at equilibrium. Now equation
(2-2) may be rewritten as
dBL/(BL-P)(BL-Q) = kadt, (2-7)
which, on integrating, gives
kat + c = (1n[(BL-P)/(BL-Q)])/(P-Q), (2-8)
where c is the integration constant determined by the initial condi
tions. If (B^)q denotes the value of B^ at t = 0 then
c = (ln[[(BL)0-P]/[(BL)0-Q]])/(P-Q). (2-9)
Upon substituting (2-9) into (2-8) we get
t = (ln[[BL-P][(BL)0-Q]/[(BL)0-P][BL-Q]])/ka(P-Q), (2-10)
and thus


42
exp [kat(P-Q)] = [Bl-P][(Bl)0-Q]/[(Bl)0-P][Bl-Q].
(2-11)
Solving for BL, we eventually find that
Bl = [P(d/e) Q exp (-ft)]/[(d/e) exp (-ft)],
(2-12)
where d = Q (B^)q, e = P (B^)q, and f = kQ(Q-P). If the initial
binding is zero (a common application), then equation (2-12) simplifies
to
Bl = [l-exp(-ft)]SLBQ/[Q-P exp(-ft)],
(2-13)
since QP = S^Bq. (This form of the solution is computationally
convenient because it avoids the generation of large exponentials as t
becomes large.)
The relative error or fractional deviation from equilibrium is
defined as
e = absolute value of [(BL~P)/P], (2-14)
and is easily calculated. If equation (2-12) and (2-14) are solved for
t (e.g., Vassent, 1974), then an expression giving the time required for
an arbitrary degree of approach to equilibrium is obtained:
t (e) = [l/ka(Q-P)] In ([QP(1-E)]/ P[l+(Q-P)/e]).
(2-15)


43
We now examine some applications of the rate equation and its
solution. In the following discussions we shall assume that Bq remains
constant with time (unless a deliberate dilution or concentration is
performed). Many in vitro steroid receptor preparations do not,
however, possess this stability. For example, a frequent observation
has been the gradual inactivation or loss, with time, of unoccupied
(free) receptor binding sites (e.g., Luttge et al., 1982). If this is
the case, then the rate equation (2-1) must be supplemented with the
simultaneous inactivation equation
d(BQ-BL)/dt = -kin (Bq-Bl) dBL/dt,
(2-16)
where k^n is an empirical inactivation constant describing a process of
simple unimolecular decay of the normal binding site conformation.
(This assumption has, of course, no theoretical basis; it is merely a
statement of the observation that the relative early regions of slow
receptor inactivation curves may be approximately fit to simple
exponentials.) Equation (2-16) simplifies to
(2-17)
which may be solved simultaneously with the rate equation (2-1) by
standard computerized numerical integration methods (e.g., Yeakley et
al., 1980).


44
Applications and Discussion
If the chosen binding assay can be performed rapidly then the
association rate constant may be determined conveniently by measuring
as a function of t for a relatively short period of time (during which
dissociation may be neglected) following the mixing of ligand with the
receptor preparation. If t is small then dissociation may be neglected
and equation (2-1) becomes simply
dBL/dt = ka(SL-BL)(B0-BL), (2-18)
which, upon integration with the initial condition that B^=0 at t=0,
gives
kat = [1/(SL-B0)] In ([B0(Bl-Sl)]/[Sl(Bl-B0)]). (2-19)
It follows immediately that
kat (SL-B0) = In (Bq/Sl) + In [(SL~BL)/(BQ-BL)]. (2-20)
It is apparent that at short times a plot of In [(S^-BL)/(Bq-B^)3 as a
function of time will be a line with slope ka (S^-Bq). The ordinate of
this plot is more easily remembered as In [(free 1igand)/(free
receptor)]. This method for the determination of k, obviously requires
both knowledge of and an estimate of Bq derived from an equilibrium
experiment performed with the same receptor preparation.
It is also possible to determine the association constant kfl by
measuring B^ following brief incubations of constant (short) duration


45
conducted at different ligand concentrations. These values of B^, when
divided by the incubation time, are taken as estimates of the initial
rate of increase of binding (dBL/dt), which is plotted on the ordinate
as a function of the total ligand S^. To analyze this experimental
strategy we note that since B^ = 0 at t = 0, equation (2-1) reveals that
the initial rate of appearance of bound complex is given simply by
dBL/dt (at t=0) = BQkaSL. (2-21)
Thus, the plot of dB^/dt (initial) as a function of is a line
possessing slope Bq^. In fact, the observed curvature of such a plot
(a decrease in slope at high values of S^) has even been offered as
possible evidence that the glucocorticoid receptor binding process may
involve multiple steps and unobserved transient intermediate states
(Pratt, Kaine and Pratt, 1975). (The most probable explanation of this
anomaly is that the constant incubation time was too long to provide a
reliable estimate of the initial dB^dt at the high ligand
concentrations.) The two aforementioned experimental designs may be
combined, of course, by accumulating the early regions of temporal
binding curves generated at different ligand concentrations. The
individual binding curves will generate independent measurement of k
d
that should not be correlated with the ligand concentration S^.
Information (in the form of the derived values of k ) from the
cl
individual binding curves may also be merged by plotting (l/BgJdB^/dt
(initial) = kfl as the ordinate vs. as the abscissa for each
binding curve. The plot should pass through the origin, and the
resulting slope provides the merged estimate of k .
d


46
The dissociation rate constant kd is determined by simply measuring
the bound ligand as a function of time following some manipulation
that prevents any further association (or reassociation) of labeled
ligand with the receptors. Ordinarily this is accomplished by adsorbing
the free labeled steroid onto activated charcoal, followed by either
dilution of the preparation to further reduce the concentration of free
steroid to a negligible level or by the addition of a high concentration
of unlabeled steroid to dilute the specific activity of any remaining
labeled free steriod (and to dilute the labeled steroid that is released
into the free pool during the course of dissociation). Thus, since the
association of labeled ligand is blocked, equation (2-1) becomes
dBL/dt = kdBL, (2-22)
where B^ now represents only labeled bound ligand. Upon integration we
obtain the familiar first order dissociation relations
ln[BL/(BL)0] = kdt (2-23)
and finally
Bl = (Bl)q exp (-kdt), (2-24)
where (B^)q is the initial bound concentration at the beginning of the
dissociation period. The rate constant kd is simply the slope of the
plot of 1 n[B^/(Bj^)q] as a function of t. The dissociation rate is also
frequently reported as the half-life (t^) of the bound complex:


47
t1/2 = 0" 2)/kd. (2-25)
Depending on the experimental design, a measurement of the
dissociation rate constant may be performed under conditions of
decreasing, constant, or increasing receptor occupancy (B^/Bg). If no
unlabeled steroid is added, the occupancy obviously will decline.
(However, if unoccupied receptors are inactivated or degraded at a rate
comparable to the dissociation rate, then occupancy will not decline as
rapidly as B^ itself.) If the receptors are saturated at t=0, then
addition of a large amount of unlabeled ligand will maintain the high
level of binding. If the receptors are not initially near saturation,
then the addition of unlabeled steroid will lead to a condition of
rapidly increasing occupancy. If necessary, the concentration of
unlabeled ligand may be chosen to maintain a desired intermediate level
of occupancy. If the dissociation kinetics are biphasic or complex
under conditions of constant occupancy or saturation, then the
possibility of several classes of binding sites must be considered
(e.g., Weichman and Notides, 1979). If the kinetics are complex under
conditions of declining occupancy, then the possibility of cooperativity
must be considered; the experiment should then be repeated at high or
constant occupancy to see if the apparent cooperativity is really a
reflection of heterogeneity (e.g., DeMeyts, Roth, Neville, Gavin and
Lesniak, 1973).
If excess unlabeled steroid is not added to the preparation at the
beginning of the dissociation period, the possible reassociation of
newly-dissociated labeled ligand or the association of the small amount
of residual labeled steroid not removed initially may reduce the


48
measured apparent dissociation constant. The magnitude of this
reduction may be estimated approximately by using the solution to the
rate equation to monitor the relaxation of to the new, low-but-
nonzero value of P (equilibrium value of B^) in the following way.
First, assume for kd the (underestimated) value that has been measured
experimentally; call this value ^(apparent). A previously estimated
value of k or K.. must also be assumed; if a value of k is assumed,
a ql a
then KdL is taken to be kd(apparent)/ka. Measured values of SL, Bq, and
(B^)q are also available. Now equation (2-12) is used with these values
of the independent variables to calculate B^ for the same values of t at
which actual measurements of BL have been made. These calculated values
of B^(t) are then used to derive, from the slope of a plot of t vs. In
[calculated BL(t)/(BL)g], another underestimated dissociation rate
I I
constant, called k^. Next assume simply that the amount by which kd
underestimates kd(apparent) is equal to the amount by which kd(apparent)
underestimates the "true" value of kd that is sought. Thus
I
"true" kd kd(apparent) ^ kd(apparent) kd, (2-26)
and finally
"true" kd jv 2 kd(apparent) kd. (2-27)
This rough estimate of the correction is reasonable when is small.
The solution to the rate equation may also be used to predict the
error in a determination of derived from a "nonequilibrium" isotherm
generated by measurements performed before equilibrium has been attained
in the incubation vessels containing the lower concentrations of S^.


49
(Estimates of the rate constants and Bq are required, of course, in
order to perform this simulation.) A predicted value of BL is calcu
lated for each experimental value of SL (at the constant value of t used
for the incubation) using equation (2-13), and the resulting values are
used to construct the predicted (curved) Scatchard plot resulting from
the inadequate incubation time. A line is fitted to the points by the
same technique that is used to fit the experimental points (e.g., linear
regression), and a value of is derived from the resulting "slope"
(e.g., right inset to fig. 4-10). The entire procedure may be iterated
for different values of t in order to simulate the approach of the
apparent, measured KdL to its "true" equilibrium value as the incubation
time is prolonged. It is instructive to examine the dependence of the
relative error function upon S^; when combined with equation (2-13),
equation (2-14) becomes
e = (Q-P) exp(-ft)/[Q-P exp(-ft)], (2-28)
which is plotted as a function of in fig. 4-10 (left inset) for
several different incubation times using one specific set of the other
independent variables. It is apparent that e rises rapidly to a maximum
and then declines slightly as is decreased from a high concentration.
Thus, as is decreased below the transition zone, e becomes essen
tially constant at a value given by equation (2-29) below, which is
simply the limiting value of e as declines:
lim e (as is decreased) = exp(-ft) = exp C-kQt(].
(2-29)


50
Thus, if a time and receptor concentration Bq are chosen such that
equation (2-29) is reduced to an acceptable level, then very low values
of may be used to generate an isotherm. (More rigorously, one may
find by setting equal to 0 the partial derivative of equation (2-28)
with respect to S^, the exact nonzero value of that maximizes e; then
a time may be chosen that reduces this maximum relative error to an
acceptable level.)
Predicting the effect of the addition of a competing, cold ligand
(C) on the rate of approach to equilibrium of is a more complex
problem; this calculation requires the numerical integration of the two
simultaneous rate equations
dBL/dt = ka (B0-Bl-Bc)(Sl-Bl) kdBL (2-30)
and
dBc/dt kaC (Bq-Bl-Bc)(Sc-Bc) kdcBc, (2-31)
where the subscript C refers to the competing ligand. Several
qualitative inferences can be drawn, however, from the fact that the
only effect of the competitor C is to decrease the free receptor
concentration in equation (2-30). Consider now the relative error e as
a function of Bq rather than of S^; since and Bq appear symmetrically
in equation (2-28), the left inset to fig. 4-10 also portrays the shape
of the plot of e considered as a function of Bq (with now held
fixed). If is sufficiently large, then the position of Bq will be to
the left of the maximum value of e on the plot; if is small enough,


51
however, the position of the same value of Bq will now be to the right
of the e maximum value. Thus, depending on the relations among S^, Bq
and K^, the effect of the reduction of free receptor concentration by
the competing ligand can be either to increase, decrease, or leave
essentially unchanged the value of e at a given time. Under the right
conditions a competitor may easily increase £ from near 0 to the maximum
value consistent with the given values of and t. (The rate constants
for ligand C and its concentration will, of course, affect £ by
determining how fast the competitor depletes the free receptor
concentration.) A very rough estimate of the effect of a high-affinity
competing ligand on the time required for B^ to approach equilibrium may
be obtained simply by assuming that the competitor is identical to the
labeled ligand. In this simple case becomes the sum of the labeled
and competing ligands, and equation (2-28) predicts £ for the total
bound ligand (B^ + Bq) for different times. Clearly this value of the
relative error also applies to B^, since for this special case
bL = SL (Bl+Bc)/(Sl+Sc). (2-32)
In order to facilitate estimation of the times required for the
approach to equilibrium under a variety of conditions, we present in
table 2-1 a short summary of solutions to the rate equation (2-1) for
several useful combinations of the variables Bq, S^, and (i.e.,
kj/ka) for the case of a single ligand and binding site. The initial
condition is simply (B^)q = 0, and the solution is presented as a table
of pairs of numbers representing the number of hours required for B^ to
attain 80% and 95%, respectively, of the equilibrium value. These


Table 2-1. Number of hours required for the concentration of specifically-bound ligand (B^) to reach 80%
and 95% (upper and lower number in each pair, respectively) of true equilibrium for a noncooperative, single
site binding system in which the second-order rate constant (k) equals lO^M'^min"^. For other values of
5 a
k multiply the tabulated values by 10 and divide the product by k Bn is the total number of binding
a a U
sites, is the total ligand concentration and K^. is the equilibrium constant.
-Log b 0
7
8
9
10
11
7
8
9
10
11
7
8
9
10
11
7
8
9
10
11
6
0.28
0.53
0.27
0.50
0.27
0.49
0.27
0.49
0.27
0.49
0.28
0.54
0.27
0.50
0.27
0.50
0.27
0.50
0.27
0.50
0.28
0.54
0.27
0.50
0.27
0.50
0.27
0.50
0.27
0.50
0.28
0.54
0.27
0.50
0.27
0.50
0.27
0.50
0.27
0.50
6.5
0.96
1.90
0.83
1.56
0.82
1.53
0.82
1.53
0.82
1.53
1.01
2.02
0.86
1.61
0.85
1.58
0.85
1.57
0.85
1.57
1.02
2.03
0.86
1.61
0.85
1.58
0.85
1.58
0.85
1.58
1.02
2.03
0.86
1.61
0.85
1.58
0.85
1.58
0.85
1.58
7
2.74
5.96
2.52
4.76
2.45
4.56
2.44
4.54
2.44
4.54
4.54
12.41
2.79
5.30
2.67
4.98
2.66
4.95
2.66
4.94
5.78
20.34
2.82
5.36
2.69
5.02
2.68
4.99
2.68
4.99
6.35
26.62
2.83
5.36
2.70
5.03
2.68
5.00
2.68
4.99
7.5
2.70
5.29
6.56
12.61
6.47
12.07
6.45
12.00
6.44
12.00
3.15
6.29
9.55
18.97
8.34
15.61
8.23
15.33
8.22
15. 31
3.21
8.42
10.09
20.19
8.59
16.08
8.47
15.77
8.46
15.74
3.21
6.43
10.15
20.32
8.62
16.13
8.49
15.82
8.48
15.79
8
2.52
4.76
11.07
21.22
13.24
24.74
13.40
24.94
13.41
24.96
2.79
5.30
27.44
59.62
25.21
47.65
24.47
45.61
24.39
45.41
2.82
5.36
45.37
124.1
27.92
52.95
26.69
49.76
26.57
49.47
2.83
5.36
57.77
203.5
28.23
53.56
26.93
50.22
26.81
49.91
8.5
2.46
4.61
12.79
24.12
19.41
36.23
20.28
37.76
20.37
37.92
2.70
5.05
26.96
52.90
65.61
126.1
64.66
120.7
64.47
120.0
2.72
5.10
31.48
62.86
95.51
189.7
83.39
156.1
82.34
153.4
2.73
5.10
32.05
64.16
100.9
201.9
85.91
160.8
84.69
157.7
9
2.45
4.56
13.24
24.74
22.59
42.10
24.20
45.04
24.37
45.35
2.67
4.98
25.21
47.65
110.7
212.2
132.4
247.4
134.0
249.4
2.69
5.02
27.92
52.95
274.4
596.2
252.1
476.5
244.7
456.1
2.70
5.03
28.23
53.56
453.7
1241
279.2
529.5
266.9
497.6
9.5
2.44
4.55
13.36
24.90
23.79
44.31
25.76
47.96
25.98
48.35
2.66
4.95
24.64
46.09
127.9
241.2
194.1
362.3
202.8
377.6
2.68
5.00
26.97
50.49
296.6
529.0
656.1
1261
646.6
1207
2.69
5.00
27.23
50.98
314.8
628.6
955.1
1897
833.9
1561
10
2.44
4.54
13.40
24.94
24.20
45.04
26.30
48.96
26.53
49.39
2.66
4.95
24.47
45.61
132.4
247.4
225.9
221.0
242.0
450.4
2.68
4.99
26.69
49.76
252.1
476.5
1107
2122
1324
2474
2.68
5.00
26.93
50.22
279.2
529.5
2744
5962
2521
4765
10.5
2.44
4.54
13.41
24.96
24.33
45.28
26.48
49.28
26.71
45.72
2.66
4.94
24.41
45.46
133.6
249.0
237.9
443.1
257.6
479.6
2.68
4.99
26.60
49.54
246.4
460.9
1279
2412
1941
3623
2.68
4.99
26.84
49.99
269.7
505.0
2696
2590
6561
12612
11
2.44
4.54
13.41
24.96
24.37
45.35
26.53
49.39
26.77
49.83
2.66
4.94
24.39
45.41
134.0
249.4
242.0
450.4
263.0
490.0
2.68
4.99
26.57
49.47
245.0
456.1
1324
2474
2259
4210
2.68
4.99
26.81
49.91
267.0
498.0
2521
4765
11071
21217
11.5
2.44
4.54
13.41
24.96
24.38
45.38
26.55
49.42
26.79
49.86
2.66
4.94
24.39
45.40
134.1
249.6
243.3
452.8
264.8
492.8
2.68
4.99
26.56
49.44
244.1
454.6
1336
2490
2379
4431
2.68
4.99
26.80
49.89
266.0
494.4
2464
4609
12793
24116
12
2.44
4.54
13.41
24.96
24.38
4 5.39
26.56
49.43
26.79
49.87
2.66
4.94
24.39
45.39
134.1
249.6
243.7
453.5
265.3
493.9
2.68
4.99
26.56
49.44
243.9
4 54.1
1340
2494
2420
4504
2.68
4.99
26.80
49.88
265.7
494.7
2447
4561
13235
24743
Log KdL
8
- L9 KdL
- 9
- L9 KdL
- 10
- L9 KdL 11
(J1
ro


Table 2-2. Fraction of specific binding sites occupied and the fraction of the total ligand
involved in that binding at equilibrium for a noncooperative, single site binding system.
Tabulated data are expressed as percentages with B^/Bg (x100) presented as the upper and
B^/S^ (xlOO) as the lower number in each pair. is the concentration of specifically-
bound ligand, Bg is the total number of binding sites, is the total ligand concentration
and is the equilibrium constant.
- Log bq
7
8
9
10
11
7
8
9
10
n
7
8
9
10
n
7
8
9
10
11
98.9
99.0
5975
99.0
99.0
99.9
99.9
997T
9 9.9
99.9
>99.3
>9975
>99.9
>99.9
">99.9
>99.9
>99.9
>99.9
>99.9
>99.4
9.9
1.0
0.1
<0.1
<0.1
10.0
1.0
0.1
<0.1
<0.1
10.0
1.0
0.1
<0.1
<0.1
10.0
1.0
0.1
<0.1
<0.1
95.7
96.8
96.9
96.9
96.9
99.5
99.7
99.7
99.7
99.7
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
30.2
3.1
0. 3
<0.1
<0.1
31.5
3.2
0.3
<0.1
<0.1
31.6
3.2
0.3
<0.1
<0.1
31.6
3.2
0.3
<0.1
<0.1
73.0
90.1
90.8
90.9
90.9
90.5
98.9
99.0
99.0
99.0
96.9
99.9
99.9
99.9
99.9
99.0
99.9
>99.9
>99.9
>99.9
73.0
9.0
0.9
0.1
<0.1
90.5
9.9
1.0
0.1
<0.1
96.9
10.0
1.0
0.1
<0.1
99.9
10.0
1.0
0.1
<0.1
27.8
71.0
75.5
75.9
76.0
31.2
95.7
96.8
96.9
96.9
31.6
99.5
99.7
99.7
99.7
11.6
99.9
99.9
>99.9
>99.9
87.8
22.5
2.4
0.2
<0.1
98.6
30.2
3.1
0.3
<0.1
99.8
31.5
3.2
0.3
0.1
99.9
31.6
3.2
0.3
0.1
9.0
38.2
48.8
49.9
50.0
9.9
73.0
90.1
90.8
90.9
10.0
90.5
98.9
99.0
99.0
10.0
96.9
99.9
99.9
99.9
90.1
38.2
4.9
0.5
<0.1
98.9
73.0
9.0
0.9
0.1
99.9
90.5
9.9
1.0
0.1
>99.9
96.9
10.0
1.0
0.1
2.9
14.6
22.7
23.9
24.0
3.1
27.8
71.0
75.5
75.9
3.2
31.2
95.7
96.8
96.9
1.2
31.6
99.5
99.7
99.7
90.7
46.1
7.2
0.8
0.1
99.9
87.8
22.5
2.4
0.2
99.9
98.6
30.2
i.i
0.3
>99.9
99.8
31.5
3.2
0.3
0.9
4.9
8.4
9.0
9.1
1.0
9.0
38.2
48.8
49.9
1.0
9.9
73.0
90.1
90.8
1.0
10.0
90.5
98.9
99.0
90.8
48.8
8.4
0.9
0.1
99.0
90.1
38.2
4.9
0.5
99.9
98.9
73.0
9.0
0.9
>99.9
99.9
90.5
9.9
1.0
0.3
1.6
2.8
3.0
1.1
0.3
2.9
14.6
22.7
23.9
0.3
3.1
27.8
71.0
75.5
0.1
3.2
31.2
95.7
91.1
90.9
49.6
8.9
1.0
0.1
99.0
90.7
46.1
7.2
0.8
99.9
99.0
87.8
22.5
2.4
>99.9
99.9
98.6
30.2
3.1
0.1
0.5
0.9
1.0
1.0
0.1
0.9
4.9
8.4
9.0
0.1
1.0
9.0
38.2
48.8
0.1
1.0
9.9
73.0
90.1
10
90.0
49.9
9.0
1.0
0.1
99.0
90.9
48.8
8.4
0.9
99.9
99.0
90.1
38.2
4.9
>99.9
99.9
98.9
73.0
9.0
<0.1
0.2
0.3
0.1
0.3
<0.1
0.3
1.6
2.8
3.0
<0.1
0.3
2.9
14.6
22.7
<0.1
0.3
3.1
27.8
71.0
10.5
90.9
50.0
9.1
1.0
0.1
99.0
90.9
49.6
8.9
1.0
99.9
99.0
90,7
46.1
7.2
>99.9
99.9
99.0
87.8
22.5
<0.1
<0.1
0.1
0.1
0.1
<0.1
0.1
0.5
0.9
1.0
<0.1
0.1
0.9
4.8
8.4
<0.1
0.1
1.0
9.0
38.2
11
90.9
50.0
9. 1
1.0
0.1
99.0
90.9
49.9
9.0
1.0
99.9
99.0
90. 8
48.8
8.4
>99.9
99.9
99.0
90.1
38.2
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
0.2
0.3
0.3
<0.1
<0.1
0.1
1.6
2.8
<0.1
<0.1
0.3
2.9
14.6
11.5
99.9
50.0
9.1
1.0
0.1
99.0
90.9
50.0
9.1
1.0
99.9
99.0
90.9
49.6
8.9
>99.9
99.9
99.0
90.7
4 6.1
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
0.1
0.1
<0.1
<0.1
0.1
0.5
0.9
<0.1
<0.1
0.1
0.9
4.9
12
90.9
50.0
9.1
1.0
0.1
53.0
90.9
50.0
3.1
1.0
99.9
99.0
90.9
49.9
9.0
>99.9
99.9
99.0
90.8
48.8
-Log
*<14.
8
-
k 9
. i
FI
lO
KdL '
10
-Log XdL
- 11
cn
co


54
5 -1 -1
durations were calculated for k = 10 M min For other values of
a
c
simply multiply the tabulated values by 10 and divide the resulting
product by kQ. Table 2-2 presents estimates of the fractional occupancy
of the binding sites (B^/Bq) and the fraction of the ligand bound at
equilibrium (P/S^) under the same hypothetical conditions as in
table 2-1. (These percentages apply to all values of k .)
d


CHAPTER III
LINEARIZATION OF THE TWO LIGAND-SINGLE BINDING SITE
SCATCHARD PLOT AND "ED" COMPETITION DISPLACEMENT
PLOT: APPLICATION TO iHE SIMPLIFIED GRAPHICAL
DETERMINATION OF EQUILIBRIUM CONSTANTS
Introduction
The affinity of a ligand for a particular class of binding sites is
measured frequently by constructing an isotherm describing the binding
of an available labeled ligand having specificity for the same set of
binding sites, first in the absence and then in the presence of a fixed
total concentration of the unlabeled competitive inhibitor whose
affinity constant is to be estimated (e.g., Ginsburg, MacLusky, Morris
and Thomas, 1977; Katzenellenbogen, Katzenellenbogen, Ferguson and
Krauthammer, 1978; Kono, 1975; for review of competition experimental
designs see Rodbard, 1973). The data resulting from such an experiment
are often analyzed by making the approximation that the concentration of
free competitive inhibitor is equal to the total concentration present
and therefore constant over the entire range of labeled ligand
concentration, since the effect of a constant concentration of free
competitive inhibitor on a Scatchard plot (Scatchard, 1949) describing
the binding of a labeled ligand to a single class of noncooperative
binding sites is solely to decrease the slope of the plot by a factor
which, in combination with the concentration of free competitive
inhibitor, yields immediately the equilibrium constant of the inhibitor
55


56
(Cantor and Schimmel, 1980). Thus, if the above approximation is valid,
then the affinity of the competitor results directly from the slopes of
the two straight lines and the total concentration of the inhibitor.
However, if the competitive inhibitor is not present in great excess
over the total concentration of binding sites, then the above
approximation will not be valid, the resulting Scatchard plot will be
curved (Feldman, 1972), and the error in the derived equilibrium
constant caused by making the approximation may be substantial. In the
present communication we suggest a simple procedure for eliminating this
error by linearizing the curved Scatchard plot resulting from this
experimental design.
The very popular competition displacement experimental design
(known as the "ED^q" method) also generates data that are somewhat
difficult to analyze in the laboratory without the aid of computerized
nonlinear regression techniques. Within this design one measures the
fraction of initially bound labeled ligand remaining bound at
equilibrium in the presence of increasing concentrations of the
unlabeled competitive inhibitor whose affinity is to be measured (e.g.,
Abrass & Scarpace, 1981; Lindenbaum & Chatterton, 1981; for review, see
Rodbard, 1973). The total concentration of inhibitor that displaces
half the initially bound labeled ligand ("ED^g") is determined, and one
then attempts to relate this inhibitor concentration to its actual
affinity for the binding sites. This design presents two major
problems: the curvature of the displacement plot makes the precise
determination of ED^g difficult, and the ED5Q itself is often quite
different from, and difficult to relate to, the actual equilibrium
dissociation constant of the competing ligand. In many situations the


57
curvature of the competition displacement plot cannot be eliminated
simply by performing a "logit-log" transformation (e.g., De Lean, Munson
and Rodbard, 1978) of the data. Furthermore, the use of approximations
(e.g., the Cheng-Prusoff (1973) formula) to relate the estimated ED5Q to
the equilibrium dissociation constant of the competitor is often
inappropriate and can lead to substantial additional error.
We now suggest that if the initial receptor occupancy is not too
high this experimental design can also be analyzed without approximation
by the simple procedure (to be described) that we recommend for
linearization of the curved, two-ligand Scatchard plot obtained in the
presence of a fixed concentration of competitive inhibitor. With this
method the equilibrium dissociation constant is obtained directly,
obviating calculation of the ED^q value itself. Furthermore, a more
nearly exact approximation that can be used to relate ED^q estimated
from an approximately linear logit-log plot of the competition
displacement data to the actual affinity of the competitive inhibitor
for the binding sites is presented. This method is particularly useful
when the initial receptor occupancy is rather high.
Theory and Application
The nomenclature for the two ligand-one binding site problem will
be as follows: and are, respectively, the concentrations of
specifically bound labeled ligand L and competitive inhibitor C. The
total concentration of binding sites is Bq. The equilibrium
dissociation constants for the binding of the labeled ligand and
competitor are, respectively, and K^; and and are the total
concentrations of these ligands. The free (unbound) concentrations of


Fig. 3-1. Theoretical Scatchard plots for a single ligand and for two ligands in
competition for one class of noncooperative binding sites. Inset:
linearization of the curved Scatchard plot by plotting the total concentration
of occupied binding sites (B^+Bq) on the abscissa.
The parameters used to generate the plots describe the binding of estradiol (E^) and
estriol (Eg) to the nonactivated calf uterine estrogen receptor and were taken from
Weichman and Notides (1980). Upper straight line: E9 alone, equilibrium dissociation
-10 ^
constant = 1.7 x 10 M; lower curved plot: E^ in the presence of 1 nM estriol (E^,
equilibrium constant = 2.6 x 10~^M). The concentration of binding sites (Bq) is 2.3
nM. The curved Scatchard plot for the purely competitive two ligand situation is a
hyperbola whose properties have been described (Feldman, 1972). The actual points on the
curve are purely hypothetical and were placed on the plot to indicate how specific binding
values map into the linearized coordinate systems shown in the inset and in Fig. 3-2 and
discussed in the text. The slope of the transformed plot remains the same (-l/KdL) as
that of the original linear plot generated by the single labeled ligand (E^), as does the
intercept on the x-axis (Bq).


15-
15
1.0
Bl (nM)
0.5
cn
X>


60
the ligands are Fq and Fq. In order to discuss the "ED5q" experimental
design we let (Bq)q and (Fq)q represent the initial values of and Fq
when Sq=0. ED^q is the value of Sq when Bq has been reduced by half
(i.e., when B = (Bq)q/2), and we let F^q and Fq^q represent the
corresponding values of Fq and Fq (i.e., when Sq = ED^q).
As the first illustrative example we have used the equilibrium
dissociation constants that describe the binding of estradiol (E2) and
estriol (E^) to the nonactivated calf uterine cytosol estrogen receptor
(Weichman and Notides, 1980) in order to generate the purely
hypothetical Scatchard plots (Fig. 3-1) of theoretical data that would
be observed for the binding of labeled E^, first in the absence and then
in the presence of Sq = 1 nM "cold" E^. (The experimental design under
discussion here was not employed by Weichman and Notides (1980); we have
merely used the affinity constants, which were measured and reported
appropriately by these authors.) The concentration of binding sites
Bq = 2.3 nM is also taken from Weichman and Notides (1980); the
equilibrium constants are KdL = 1.7 x 10~^M (for E^) and
= 2.6 x 10~^M (for E^). The linear Scatchard plot (for the case
Sq = 0) is, of course, described by the standard equation (e.g.,
Rodbard, 1973; Scatchard, 1949):
Bl/FL /KdL f3-1)
and thus has slope (-1/K^) and intercept Bq on the x-axis (Fig. 3-1).
The lower, curvilinear Scatchard plot (Fig. 3-1) for the purely
competitive two ligand situation is a hyperbola whose geometric


61
properties have been described by Feldman (1972) and whose equation is
(Feldman, 1972; Rodbard and Feldman, 1975)
BL/FL Kdct-1-(BL+SC-Bo)/KdC+['1-[BLtSC-V/Kdc)2
+ 4VKdc]1/2l/2KdL- <3-2>
This hyperbolic Scatchard plot has one asymptote with slope (-l/KdL)
parallel to the linear Scarchard plot and an x-intercept (Bq-S^.), and
another horizontal asymptote below the x-axis at BL/FL = (-K^/K^).
The actual points on the curve are completely hypothetical and have been
calculated and placed on the plot at equally spaced intervals of
(0.275 nM) in order to indicate how specific binding values map into the
modified coordinate systems to be discussed.
We now calculate the error in the derived value of resulting
from the assumption that the concentration of free inhibitor F^ is
constant in this experiment and therefore that the expression (derived
from simple Michaelis-Menten kinetics for the case of pure competitive
inhibition) sometimes called the Edsall-Wyman equation (Cantor and
Schimmel, 1980) is valid when applied to some estimate of the "slope" of
this (actually curved) plot. The Edsall-Wyman equation can be
rearranged to the convenient "Scatchard" form given by
(cf. equation 3-1)
Bl/Fl - (BL-B0)/KdL(l+Fc/Kdc).
(3-3)


62
Thus, it predicts simply that the slope of the Scatchard plot will be
reduced by a factor of 1/(1+Fc/Kdc) in the presence of a constant
concentration of free inhibitor F^. We now substitute the total
concentration for the (actually variable) free concentration Fj,.
Thus, the estimated value of KdC derived from the use of this
approximation (which we call K^app) will be given by
Kdc(app) = [reduced slope/(original slope-reduced slope)]S^.
(3-4)
Thus, the percentage error (E) will be given by
E/100 = [KdC(app)/KdC]-l (3-5)
and hence, from above,
E/100 = reduced slope)/Kd^[l+Kd^(reduced slope)]-l.
(3-6)
For the "reduced slope" we substitute the derivative of the equation of
the curvilinear Scatchard plot, d(B^/FL)/dB^, obtained directly from
equation (3-2) above. Thus, if the error is estimated by using as the
"reduced slope" the slope of the tangent to the curve at the abscissa
B^ = Bq/2, then the error in the derived equilibrium constant is given
explicitly by
E/100 = (Kdc[Sc-Kdc]Y-X[Sc+Kdc])/(Kdc2Y+KdcX),
(3-7)


63
where X = S^-K^^-Bq/Z) and
Y ([l-(2Sc-B0)/2Kdc]2+4Sc/Kdc)1/2.
Thus, the error is independent of and vanishes under the ideal
conditions approached when Bq and In the hypothetical
example involving estradiol (E^) and estriol (E^) the error resulting
from the use of this approximate method is large: the derived
(calculated from the slope obtained from a linear regression on the
eight hypothetical points shown on the curvilinear Scatchard plot in
-9
Fig. 3-1) for E3 is 1.6 x 10 M, whereas the actual value used to
generate the curve is 2.6 x 10~^M, a 5-fold discrepancy. In fact, a
significant and variable fraction of the competitor E^ is obviously
bound to the receptors in this hypothetical experiment.
The error discussed above may be avoided by analyzing the data from
the same experimental design in a slightly different manner. At
equilibrium the simple mass action rate equations for the binding of the
two ligands may be written as
(B0-BL-BC)FL KdLBL and
(3-8)
0 L C' L
(3-9)
which suggest immediately the "linearized Scatchard" forms given by
BL/FL = [(BL+BC)_B0]/KdL and
(3-10)


64
VFC ^BL+BC^"B0^KdC (3-H)
Thus, if B^/F^ or Bq/Fq on the ordinate are plotted against (Bq + Bq) on
the abscissa, then a linear "Scatchard-1 ike plot with slope (-1/K^) or
(-1/Kdc) and x-intercept Bq results (insets to Figs. 3-1 and 3-2).
Furthermore, since Bq (as well as K^) is derived from an initial
Scatchard plot constructed in the absence of the competitor, K^q may be
measured simply by plotting [Bq-Bq-Bq, (free binding sites)] on the
abscissa against Bq/Fq on the ordinate, as suggested by equation (3-9).
The resulting plot (Fig. 3-2) must pass through the origin and possess
slope (1/K^q). This is the analysis we recommend for the determination
of KdC by this experimental method.
The implementation of this analysis is scarcely more difficult than
the method that we have criticized: the only additional requirement is
the calculation of Bq and Fq for each data point. We note that Bq and
KdL have been determined already from an initial Scatchard plot.
Equation (3-8) is now rearranged to give
Vbl'bc KdiA/FL- <3-12>
Thus, the abscissa of the recommended plot is determined directly from
equation (3-12), as is the value of Bq = [Bq-B^-(^dLBj_/F^)]. Since Sq
is known, Fq ^ Sq-Bq. (Note that nonspecific binding of the "cold"
competitive ligand must still be neglected, unless it can be estimated
from other experiments, e.g. Katzenellenbogen et al., 1978). The
best-fitting straight line passing through the origin is then fit to the
points as shown (Fig. 3-2), and the reciprocal of its slope is then


Fig. 3-2. Linearization of the curved Scatchard plot shown in Fig. 3-1.
The same hypothetical data points presented in Fig. 3-1 are shown plotted in the
coordinate system recommended for the determination of K^. The ordinate (B^/F^) now
refers explicitly to the concentrations of bound and free competitor (E^), and the
concentration of free binding sites (BQ-BL-BC) is plotted on the abscissa. The plot must
pass through the origin, and the slope (l/KdC) is the reciprocal of the dissociation
constant of the competitor (E^). The inset is analogous exactly to the inset of Fig. 3-1
the points are plotted with the total concentration of bound sites (B^B^) on the x-axis.
In this "Scatchard format" the slope is (-1/K^) and the x-intercept is again Bq.


0.5
1.0
[B0- Bl-Bc] (nM)
1.5
cn
CX>


67
determined. For statistical reasons it may be advisable simply to apply
the least squares criterion (i.e., to use the method of simple linear
regression) and not force the line to pass through the origin. Since
the plot of B^/F^ vs. [free binding sites] is used to estimate only one
binding parameter (K^), data sets arising from experimental
preparations differing in total binding site concentration may be merged
prior to the final analysis.
We have extended the analysis presented above to cover a very
limited case of the two ligand-two binding site problem: the method has
been used to "linearize" data resulting from investigation of the
specific mouse brain glucocorticoid receptor in crude cytosol containing
significant amounts of CB6 (transcortin). We have measured the affinity
of "cold" dexamethasone (which has negligible affinity for CBG) for the
specific [ Hjcorticosterone, non-CBG, binding sites (putative receptors)
in CBG-containing brain cytosol in order to compare the resulting
equilibrium constant with that obtained by using [ H]dexamethasone
itself to construct a one-ligand Scatchard plot. The experiment is
performed by first constructing separate sirigle-1 igand binding isotherms
3 3
using [ H]dexamethasone and [ Hjcorticosterone; then an isotherm
3
describing the binding of [ Hjcorticosterone in the presence of a fixed
concentration of dexamethasone is constructed and analyzed. (The same
cytosol preparation is used throughout, of course.) This analysis is
simplified dramatically both by the absence of a significant interaction
of dexamethasone with CBG and by the observation that the one-ligand
[ Hjcorticosterone Scatchard plot is not biphasic, which suggests that
the affinity of corticosterone for CBG is very similar to its affinity
for the putative receptors.


68
In order to describe the analysis we extend slightly the
nomenclature used above; this nomenclature will apply only to the
specific two-ligand, two-site isotherm to be "linearized." Bg and Bg
are the total concentrations of specifically bound [ Hjcorticosterone
and "cold" dexamethasone, respectively. BgR and BgT are the
concentrations of [ H]corticosterone bound to the putative receptors and
to CBG (transcortin), respectively. (Thus, Bg = BgR + Bgy). B^^ is
the total concentration of all binding sites, composed of Bg putative
glucocorticoid receptors and Tg transcortin binding site
(BMAX = B0 + V- KdL describes (approximately) the common affinity of
3
[ Hjcorticosterone for both the receptor and CBG binding sites, and K^g
is the equilibrium constant for the binding of dexamethasone to the
glucocorticoid receptor sites. Fg and Fg are the concentrations of
3
unbound (free) [ Hjcorticosterone and "cold" dexamethasone,
respectively.
From the mass-action equations (cf. equations 3-8 and 3-9 above) we
have the following:
(Bg-BLR-Bg)Fc = ^gBg,
(3-13)
%BLR-Bc)FL = KdLBLR
(3-14)
(VBLl)FL = KdLBLT
(3-15)
and, adding equations (3-14) and (3-15) we get
(BMAX-BL-BC>FL = KdlA-
(3-16)


69
Since dexamethasone does not bind to CBG, recall that the plot of Br/Fr
as ordinate vs. abscissa [(BQ-BLR-BC), free receptor sites] is a line
passing through the origin with slope (1/K^). This is the plot used to
find Kdc for dexamethasone by competition with [ H]corticosterone.
The calculation deriving from the competition data is
straightforward. Bq is determined from the one-ligand isotherm of
O
[ H]dexamethasone binding, and B^^^ and Kd^ are derived from the
one-ligand [ Hjcorticosterone plot; Tq is then estimated from the
relation Tq = B^-Bq. Tbe abscissa, [free glucocorticoid receptor
sites], is now rewritten as
B0BLRBC = (BMAX"BL"Bc) (T0'BI_t); (3-17)
i.e. [free receptor sites] = [total free sites]-[free CBG sites].
Substituting from equation (3-16) above we obtain for the abscissa
6 - <3-18>
Solving equation (3-15) for B^ and substituting the resulting
expression into equation (3-18) yields finally the computational form
for the abscissa:
B0"BLR~BC = Kdd VJ- <3-19>
Now only Bq must be found, since Fq and Bq/Fq follow immediately. The
calculated value of the abscissa, [free receptor sites], is used to find
Bq from the identity


70
Bg = Bq-Blr- [free receptor sites].
(3-20)
By substituting the expression for B^R obtained from equation (3-14)
into equation (3-20) above, the convenient computational form for Bg is
found to be
Bc = B0 [free receptor sites] (1+F^/K^^).
(3-21)
The estimate of K^g then follows directly from the slope of the
recommended plot described above.
We now turn to an analysis of the "ED5g" experimental design.
Figure 3-3 depicts theoretical competition displacement curves generated
by the same binding parameters (taken from Weichman and Notides, 1980)
that were employed in the construction of figs 3-1 and 3-2 and used in
the above analysis of the design in which the inhibitor is present at a
single concentration (the "Edsal1-Wyman" design). Furthermore, it is
presumed that K- and Bg have previously been measured in the absence of
competitor by constructing the one-ligand isotherm. If the initial
receptor occupancy [(B^Jg/Bg] is not too high, it is obvious that
linearization of the displacement curves may be achieved by plotting the
data in the same Bg/Fg vs. [Bg-Bg-Bg, free binding sites] coordinate
system discussed above in connection with the Edsall-Wyman experimental
design, using the same data manipulations to determine the abscissa and
ordinate of the plot (shown as inset to fig. 3-3). If the initial
receptor occupancy is too high, then the range of the plot will be
compressed severely and this method will not be useful.


Fig. 3-3. Theoretical curves for the competitive displacement of ligand L by ligand C
from a single class of noninteracting binding sites.
Upper curve: fraction B^/(Bl)q of initial bound ligand L remaining bound at equilibrium in
the presence of different concentrations (S^) of competitive inhibitor C; lower curve:
the bound/free ratio for ligand L at the various concentrations of competing ligand C.
Inset: linearization of the displacement curves by plotting the same data in the B^/F^, vs
^0~BL"BC* free binding sites] coordinate system. Again, the slope is (1/Kdc). The
binding parameters used to generate the plots are listed in the legend to fig. 3-1 and are
the same in all figures. The initial receptor occupancy depicted in the figure is 50%,
and the concentrations of competitor C are spaced equally on a logarithmic scale.


- LOG S,
-0.8
-0.6
t 1 r
0.4 0.6 0.8 I
0-Bl-Bc] (nM)
-1.0
-0.4
()
(BL>0
-0.2


73
Other methods must be used to determine from the displacement
plot when the initial receptor occupancy is too high. The direct
estimation of an ED^g value from the curved displacement plot (fig. 3-3)
is statistically naive, but a "pseudo-Hill" or logit-log transformation
of the data (fig. 3-4) may be used to approximate a straight line for
the estimation of ED^g by simple linear regression. The subsequent
calculation of dc from the ED5Q estimate presents further difficulties.
We shall consider sequentially the problems of estimating ED^g and then
using this estimate to calculate Kdg.
The "logistic" equations (see De Lean et al., 1978, for review;
these are only approximations, as we shall demonstrate) that are used to
transform the competition displacement data of fig. 3-3 into the
approximately linear logit-log plots shown in fig. 3-4 are the
foil owing:
Bl = (B(_ )0/ ( 1+Sc/ED^q ) 1 -
(3-22)
and
(3-23)
(The above Hill coefficient or "slope-factor" of 1.0 in the logistic
equations is appropriate for non-interacting binding sites such as those
under consideration here.) These logistic equations may be immediately
transformed into the "pseudo-Hill" or logit-log expressions
logit [BL/(BL)g] = log (B,_/[(BL)g-BLJ) = log ED5Q log Sg (3-24)


Fig. 3-4. Logit-log transformations of the competitive displacement data shown in
fig. 3-3.
Both curves share the same ordinate (logit [B^/(BL)q]), but the abscissae refer
respectively to the concentration of free competitor C (Fc, lower curve) and to the total
concentration of ligand C (S^, upper curve). The intersections with the dotted line
(x-intercepts) define the ED^q and F^q for the given conditions, but neither is a good
estimate of K^. The slopes of the ED^q and F^q plots determined by simple linear
regression are, respectively, -1.22 and -0.91. The nonlinearity of the ED^q logit-log
plot is quite apparent. The use of estimates of ED5Q and FC5Q to determine KdC is
discussed in the text.


2.0-
.5-
1.0-
LOG
Bl
Ebl\)_bl] -5"
0.0-
-0.5-
10.0
9.5
-LOG Fc0


76
and
logit [Bl/(Bl)0] = log (BL/[(BL)Q-BL]) = log FC5Q log Fc,
(3-25)
which may be fit (approximately) to the binding data by simple linear
regression. If equations (3-22) and (3-24) were exact, then the ED5Q
plot (upper curve, fig. 3-4) would be linear; if equations (3-23) and
(3-25) were exact, then the FC5Q plot (lower curve, fig. 3-4) would be
linear. Equations (3-23) and (3-25) are (as we will show) always better
approximations than equations (3-22) and (3-24). In the example under
consideration equations (3-23) and (3-25) provide an excellent
near-linear transformation of the binding data, as one can see upon
examination of fig. 3-4; the nonlinearity of the ED^q plot, however, is
quite apparent in this example.
We shall now derive the exact (but not computationally useful)
expression for logit [B^/(B^)q] and then note the condition under which
it may be approximated by equations (3-24) and (3-25). If the
Edsall-Wyman equation (3-3, above) is combined with the obvious initial
condition
(Bl)0 B0(FL)0/[KdL+(FL)0],
(3-26)
then we obtain, upon eliminating Bq from equations (3-3) and (3-26),
(3-27)


77
where the constant = [(FL >0 + KdL]/(FL>0 = 1 + KdL/(FL>0- Fronl
equation (3-27) we immediately obtain
BL/C(BL)0'BL] = ClFL/[KdL(1+FC/KdC)+FL(1Cl)] (3-28)
which, upon elimination of Cj from the denominator and division by
FLKdi> yields
BL/[(BL)0_BL] = (Ci/KdL)/[(1/FL)(1+FC/KdC)-(1/(FL)0)]-
(3-29)
Thus, the exact logit-log equation is given by
logit [Bl/(Bl)0] = log (Cj/K^)
- log [(1/FL)(1+Fc/Kdc)-(1/(FL)0)], (3-30)
which is not computationally useful (since the term for the logit-log
abscissa itself contains the unknown K^). If, however, we may assume
that F^ is approximately constant over the entire range of (i.e.,
that F^ % (F^)q), then equation (3-30) reduces to the simplified form
logit [BL/(BL)0] % log [C1K(jC(F,_)Q/KdL] log Fc, (3-31)
which is the linear logit-log plot equivalent to equation (3-25) above.
A comparison of equations (3-25) and (3-31) shows that the assumption F^
2 (F^)q leads to the expression


78
FC50 ClKdC^FL^O/KdL ~ KdC^1+^FL VKdlJ (3-32)
thus indicating clearly that Fg^g (and, of course, ED^g) is quite
different from the desired parameter K^g, which must be determined by an
additional calculation. Although the above approximation that leads to
linearization of the logit-log Fg plot (i.e., Fg ^ (Fg)g) is derived
from the initial occupancy condition (Bg)g << Sg, the approximate
linearity of the plot is fairly robust over a broad spectrum of
experimental conditions and depends only on the initial conditions
relating to the labeled ligand L. Specifically, the approximate
linearity of the logit-log Fg plot does not depend on the relative
affinity of the two ligands, (Kdc/KdL)* The Plot containing
log Sg as abscissa (the "ED^q" logit-log Sg plot), however, departs
significantly from linearity because the approximation Fg Sg is a poor
one at low values of Sg. If K^g >> K^g then the large values of Sg
required to achieve ligand displacement will also make this formula
approximately valid and thus lead to linearization of the simpler ED^g
plot. The calculation of Fg for the construction of the logit-log Fg
plot from the measured data has been described above (equation 3-12
combined with the relation Fg = Sg Bg), and the initial binding (Bg)g
may either be measured directly or calculated from the values of K^g and
Bg (in combination with the known Sg) measured previously. In the
specific example under consideration simple linear regressions of the
theoretical logit-log data of fig. 3-4 yield the following results:
[ED50 (lin. regress.)/"true" EDgg] = 1.12 (13% error), and [Fg5Q (lin.
regress.)/"true" Fg^g] = 0.999 (0.1% error). (The "true" values of
ED^g and Fg¡-g are, respectively, 4.80 and 3.20 nM.)


79
Further analysis is, of course, required to calculate Kdc from the
estimates of either ED^q or Fq5q obtained from the logit-log plots
discussed above. If, in equation (3-32) above, Fq5Q is replaced by ED
50
and (Fl)0 by Sq, one obtains the Cheng-Prusoff (Cheng and Prusoff, 1973;
Munson and P.odbard, 1980) correction
KdC^ ED50/(1+SL/KdL)* (3-33)
This formula is derived from equations (3-2) and (3-3) above by using
the definition of ED5Q (i.e., that (Bl)q = 2B^ when Sq = ED5Q) and
applying the drastic approximation that both Fq Sq and Fq % S. As
the illustrative example will demonstrate, this does not provide a good
estimate of when the affinity of the competing ligand is too high.
We now show that this Cheng-Prusoff correction can be improved
substantially by including in the calculation the value of (Bq)q, which
easily can be measured experimentally or calculated from the values of
KdL and Bq measured previously. Combining the above equations (3-3),
(3-23) and (3-26) yields, upon elimination of Bq, the expression
^FL^0FC50^KdL + (FlJo-^FC50+iy FL/^Kdl_(1+FC/lW+FlJ *
(3-34)
which, when evaluated at the 50% displacement point, becomes
(FL)0/2[KdL+(FL)0] a, FL5o/tKdL^1+FC50/KdC^+FL50-''
(3-35)


80
(Expressions (3-34) and (3-35) above are not exact, since they are
derived from the logistic equation (3-23), which is itself only an
approximation.) Since F^q = S|_ (Bg)g/2 and = SL ^BL^0 we
finally obtain, after elimination of F^g and (Fg)g and some
rearrangement and simplification,
KdC FC50 x 2KdL^SL"^BL^0^^BL^0 + 2SL
+ 2SLKdL-3SL(BL)0]. (3-36)
This is a much better approximation than the Cheng-Prusoff
equation (3-33), to which it reduces when (Bg)g is neglected and Fg5Q is
replaced by ED^g. Equation (3-36) remains approximately valid, and is
still superior to equation (3-33), when ED5q is substituted for F^:
KdC ^ ^ x 2KdL[V(BlV/t(Bl^)2 + 2SL2
+ 2SLKdL-3SL(BL)g]. (3-37)
Equation (3-36) will, however, always be superior to equation (3-37);
similarly, the Cheng-Prusoff expression itself will always be more
nearly exact if a good estimate of Fg5g is substituted for the estimate
of EDgg. Table 3-1 lists, for the example that we have been
considering, the K^g estimates derived from the two different
approximations; each method has been used in combination with both the
estimated and the exact values of Fg^g and ED^g listed above. It will
be seen that the retention of (Bg)g in the approximation is required for


Table 31. Estimates of KjC (The assumed exact value is 2.632 x 10^M) derived from the
Cheng-Prusoff correction and from the approximations described by equations 3-36 and
3-37. The inputs to the equations include both the exact values of F^q and ED^q for
the example discussed in the text and the estimated values derived as described from the
logit-log plots of Fig. 3-4.
Input ED50
Input FC50
Exact
Estimated
Exact Estimated
Cheng-Prusoff
method (eqn. 3-33)
5.462 x
10'10M
6.107 x 10-10M
3.648 x 10"10M 3.644 x 1010M
Method of eqns.
(3-36) & (3-37)
3.941 x
10"1M
4.406 x 1010M
2.632 x 10"10M 2.629 x 10"10M


82
the accurate derivation of KrfC from the competition displacement data
under consideration here. The ease of implementation of equation (3-36)
suggests that it (or at least equation 3-37) should always be used
instead of the Cheng-Prusoff approximation.
Although the graphical linearization of competition data is
achieved most conveniently in the recommended coordinate systems
discussed above, it can be displayed in simple modifications of any of
the popular binding plots. For example, a modified "Lineweaver-Burke"
plot (Lineweaver and Burke, 1934) that is linear with slope (and
y-intercept 1.0) can be constructed by plotting (Bq-B^J/B^ on the
ordinate with 1/F^ on the abscissa. A modified "direct linear" plot
(Eisenthal and Cornish-Bowden, 1974) may even be used to estimate by
finding the median of the abscissae of the intersections where lines
plotted for each of the individual observations in the usual "direct
linear" parameter space (F^, B^) intersect the horizontal lines having
ordinates Bq-B^.
The problem of determining the best-fitting line for the
recommended Bc/Fc vs. [Bq-Bl-Bc, (free binding sites)] plot is similar
to the problem of regression for the original one-ligand Scatchard plot
and has, in this context, been adequately discussed (e.g. Cressie and
Keightley, 1979; Rodbard, 1973; Rodbard and Feldman, 1975). In
addition, by the very nature of the definition of logit [B^/(Bl)q], the
logit-log plots of competition displacement data are quite sensitive to
error in the measurements of B^ performed at the low concentrations of
the competing ligand. Although the assumptions underlying the use of
the method of least squares (e.g., uniformity of variance,
noncorrelation of error in the independent and dependent variables) are


83
clearly violated in both the Scatchard and logit-log transformations of
the data (e.g., Rodbard, 1973), the method of least square is still used
frequently as a convenient first approximation and is probably not too
seriously biased if "outliers" are few and if confidence intervals are
strengthened by repetition of the experiment. Thus, the method of
simple linear regression or of linear regression through a fixed point
(the origin) may be applied to the recommended B^/vs [free binding
sites] plot; the calculation for the latter (Pollard, 1977) is routine
and directly yields
KdC = 1/slope = KdL?(BL/FL)1/z(BL/FL)1(Bc/Fc)i. (3-38)
The approximate analysis of variance and confidence intervals are given
in standard tests (e.g., Pollard, 1977). It is also convenient to use
the simple and more "robust" median parameter estimates discussed by
Cressie and Keightley (1979). This procedure (Cressie and Keightley,
1979) may be used to determine and Bq from the initial Scatchard
plot; and then if the line is to be forced to pass through the origin,
the "free receptor" plot for the direct determination of may be
analyzed by calculating the median estimate
KdC = 1/slope = median of (BLKdLfrc//BCFrL^i (3-39)
In any case, the statistical complexity of the experiment demands that
confidence in the parameter estimates obtained by any of the methods
discussed above must come from replication of the complete design.


84
Discussion
A simple procedure for linearizing the curved Scatchard plot of the
binding of a labeled ligand to a single class of noninteracting binding
sites in the presence of a fixed total concentration of competitive
inhibitor has been presented. Since the nonlinearity of the Scatchard
plot constructed in the presence of the inhibitor may not be apparent
upon visual inspection because of variance in the data, the method of
calculating the equilibrium constant of the competitive inhibitor
recommended above should be used unless it is known that the equilibrium
dissociation constant of the inhibitor (K^g) is much larger than the
total concentration of binding sites. The same procedure may also be
applied to the analysis of data derived from the "ED5q" competition
displacement experimental design (if the initial receptor occupancy is
not too high). In addition, a useful approximation (a generalization of
the Cheng-Prusoff formula) that may be used to relate the ED^g or F^q
estimates obtained from approximately linear logit-log plots of
competition displacement data to the actual affinity of the competitive
inhibitor for the binding sites has been presented.
Significant sources of error remain inherent in both experimental
designs and cannot be eliminated easily; these include nonspecific
binding of the competitive inhibitor and also the potential presence of
additional receptor sites having significant affinity for the
competitive inhibitor but negligible affinity for the labeled ligand.
Furthermore, the statistical characteristics of the simple graphical
methods suggested above currently remain untested and must eventually be
examined in detail by the Monte-Carlo simulation procedure (e.g. Thakur,


85
Jaffe and Rodbard, 1980); for example, the competition "free receptor"
plot is probably less sensitive to error in BQ and K^. when it is
"relaxed" (i.e., not forced to pass through the origin). Whenever
practical, a computer program (e.g., Munson and Rodbard, 1980) should be
used to fit binding isotherms by a weighted, nonlinear regression
technique performed with a relatively error-free independent variable.
The plot of B^/F^ vs [free binding sites] or the competitive
displacement logit-log plot may still be used to display the actual data
points and the fit of the resulting computer-generated parameters.


CHAPTER IV
EQUILIBRIUM BINDING CHARACTERISTICS AND HYDRODYNAMIC PARAMETERS
OF MOUSE BRAIN GLUCOCORTICOID BINDING SITES
Introduction
Glucocorticoids have profound metabolic, neuroendocrine, and
behavioral effects in the mammalian brain (for reviews, see: Bohus et
al., 1982; Rees and Gray, 1982). Although some of the less-
well -understood effects may result from direct interactions of the
steroid with components of target cell membranes, many of the effects
are thought to be mediated by interactions of the hormone molecules with
steroid-specific cytoplasmic and nuclear macromolecular receptors that
concentrate as activated hormone-receptor complexes in the target cell
nuclei, where they initiate changes in gene expression that produce the
ultimate physiological effects.
The experiments reported here examine a number of physiochemical
characteristics of soluble mouse brain glucocorticoid binding sites, in
order to determine whether the glucocorticoid receptor system in mouse
brain resembles closely that operative in other target tissues and-
species. Although a few published studies have reported the existence
of glucocorticoid receptors in the mouse brain (e.g., Finch and Latham,
1974; Nelson et al., 1976; Angelucci et al., 1980), no basic
characterization of the kinetic and equilibrium binding parameters or
the steroid specificity of these receptors has yet been reported.
86


87
Although a body of literature concerned with the properties of rat brain
glucocorticoid receptors already exists (for review, see: Bohus et al.,
1982), recent improvements in receptor methodology have made it possible
to study the brain glucocorticoid receptor system under conditions that
prevent receptor activation (nucleophilic transformation) and maximize
in vitro receptor stability, permitting the relatively lengthy
incubations and procedures required to generate equilibrium isotherms
and to investigate the size and shape of the receptors.
We have used the labeled glucocorticoids [ Hjcorticosterone,
3 3
[ H]dexamethasone and [ H]triamcinolone acetonide (cyclic acetal).
3 3
[ H]Dexamethasone and [ H]corticosterone were used to measure
equilibrium and kinetic binding parameters, whereas the
nearly-irreversible ligand [ Hjtriamcinolone acetonide ([ H]TA) was used
for the lengthy sedimentation and chromatography procedures required to
examine receptor size and shape. The experiments reported here have
explored buffer components and employed a buffer that prevents the loss
of unoccupied binding sites at 2C; used a rapid and convenient binding
assay; considered the possible consequences of failure to allow adequate
incubation time when ligand concentrations are low; compared equilibrium
binding parameters derived from the same pool of experimental data by
several different methods of analysis; determined ligand specificity by
applying mathematically correct procedures to the analysis of steroid
competition data; observed that CBG-like molecules contribute
signficantly to the total pool of corticosterone binding sites, and
examined binding site sizes and shapes to assess the stability and
homogeneity of the in vitro receptor population.


88
Materials and Methods
Chemicals, Steroids and Isotopes
The [1,2,6,7- Hjcorticosterone (SA = 80 Ci/mmole),
3 3
[6,7- Hjdexamethasone (SA = 36 Ci/mmole) and [6,7- H]triamcinolone
acetonide (SA = 37 Ci/mmole) were purchased from New England Nuclear
(Boston, MA) and checked for purity by chromatography on 60 cm LH-20
columns (Sippell, Lehmann and Hollmann, 1975) or by thin layer
chromatography (TLC) on Silica Gel G (plates were developed in
cyclohexane : methyl ethyl ketone, 1:1, or in dichloromethane :
methanol, 24:1). All nonradioactive steroids were purchased from
Steraloids, Inc. (Wilton, NH). Additional radiochemicals
([^Cjantipyrene, [2-^H]deoxy-D-glucose, [^C]formaldehyde,
[carboxyl-^Cjinulin and [^Hjwater) and a [^Ijcortisol Solid Phase
Radioimmunoassay kit were purchased from New England Nuclear.
Chromatography and filtration supplies were purchased from Pharmacia
Fine Chemicals (Piscataway, NJ), Bio-Rad Laboratories (Richmond, CA),
Whatman, Inc. (Clifton, NJ), Brinkmann Instruments, Inc. (Westbury, NY),
and the Amicon Corp. (Danvers, MA). Rabbit antiserum to corticosterone
was a gift from R.H. Underwood and G.H. Williams (Peter Bent Brigham
Hospital, Boston, MA). Other chemicals and solvents were of the highest
purity available commercially.
Animals
All studies used adult female CD-I mice (outbred, 20-25g Charles
River Laboratories, Wilmington, MA) that were subjected to combined
ovariectomy and adrenalectomy 3-5 days prior to the experiment in order


89
to remove known sources of endogenous steriods. Ovariectomy and
adrenalectomy were performed bilaterally via a lateral, subcostal
approach under Nembutal anesthesia, and mice were given 0.9% NaCl in
place of drinking water. On the day of the experiment mice were
anesthetized with ether (in some cases a .5-1 ml blood sample was then
withdrawn directly from the heart) and slowly perfused (over a period of
5 min) through the heart with cold HEPES-buffered saline (3 ml,
isotonic, pH 7.6) to reduce blood-borne CBG contamination of the brain
tissue. The efficacy of this procedure was assessed by a [^Cjinulin
washout study (see Chapter V).
The effectiveness of the surgery was verified by measurement of
corticosterone levels in plasma samples obtained from some of the
adrenalectomized mice at the time of killing. This was accomplished by
radioimmunoassay (RIA) both with rabbit antiserum to corticosterone (by
a modification of the method of Underwood and Williams, 1972) and with
125
the New England Nuclear [ I]Cortisol solid phase RIA kit using corti
costerone to construct the standard curve. Plasma samples (10^,1) were
extracted with 1 ml dichloromethane and then dried down prior to RIA.
Buffers
For most of the experiments cytosol was prepared in buffer A: 20 mM
HEPES, 1 mM EDTA, 2 mM DTT, 10 mM Na2Mo04, 10% (w:v) glycerol, pH 7.6.
The effects of pH and of the dithiothreitol (DTT) and molybdate
(Na2Mo04) concentrations on binding site stability were explored in
several initial experiments, and gel filtration and sedimentation were
performed at elevated ionic strength (with the addition of KC1). In the
descriptions of these experiments buffer compositions are reported as


90
modifications of the basic buffer A formulation (e.g., buffer A DTT,
buffer A + .15M KC1, etc.).
Cytosol Preparation and Aging
Brains were removed from the perfused animals and homogenized (20
strokes at 1000 rev/min) in 1-6 volumes of cold buffer A in a glass
homogenizer with a Teflon pestle milled to a clearance between the
pestle and homogenization tube of 0.125 mm on the radius (to minimize
rupture of the brain cell nuclei, as suggested by McEwen and Zigmond,
1972). The crude homogenate was centrifuged at 2C for 10 min at 15,000
rpm (27,000 x g) in a 15 ml Corex centrifuge tube. The supernatant was
transferred to a 10 ml "Oak Ridge" polycarbonate tube, and the pellet
was washed by resuspension in half the initial volume of buffer A (used
for the homogenization) and recentrifugation at 2 C for 10 min x 27,000
g. The resulting supernatant wash was added to the original supernatant
in the "Oak Ridge" tube, which was then centrifuged at 2 C for 1 h at
106,000 x g (average) to produce the cytosol used in the incubations.
Approximately 2 h elapsed between the time of killing and termination of
the high-speed centrifugation. Cytosol protein concentrations for the
equilibrium experiments ranged from approximately 2 mg/ml (with
homogenization in 6 volumes buffer A, initial pellet then washed with 3
volumes buffer A) to 12 mg/ml (homogenization in 1 volume buffer A,
pellet washed with 0.5 volume additional buffer A). The cytosol protein
content was determined by a modification of the Lowry method (Bailey,
1967) using bovine serum albumin as the standard.
In several experiments cytosol samples were incubated without
steroid for variable lengths of time before labeling with the


91
3
[ H]steroid ligand (i.e., the cytosol was deliberately "aged" beyond the
approximately 2 h required for cytosol preparation). In such
experiments the duration of aging was measured from the time when
cytosol preparation was completed (t = 0).
In order to examine the subcellular distribution of glucocorticoid
binding sites in mouse brain the standard subcellular fractionation
scheme (Cotman, 1974) was employed to generated crude nuclear (P-|),
crude mitochondrial (P^), and microsomal (P3) fractions in addition to
the cytosol; the fractionation scheme was modified, in that buffer A
(which is hypertonic because it contains 10% glycerol) was used instead
of isotonic .32 M sucrose. The concentrations of high-affinity
glucocorticoid binding sites measured in the subcellular fractions
(other than cytosol) generated in this way were negligible, and thus
these hypertonically-produced particulate fractions were not further
characterized.
Binding Assays
O
The principal assay used to measure bound [ Hjsteroid was the DEAE
(Whatman DE-81) filter assay, modified from similar assays developed to
measure glucocorticoid and mineralocorticoid binding to cytosolic
proteins in liver and kidney (e.g., Warnock and Edelman, 1978; Santi,
Sibley, Perriard, Tomkins and Baxter, 1973). The 25 mm filters were
equilibrated at 0-4C in buffer A and then washed 2 times with 2 ml
buffer A in a Millipore suction manifold. For each of the triplicate
assays that commonly were performed a 50 ul aliquot of the sample was
pipeted directly onto the moist filter and allowed to penetrate it for
at least 1 min. Filters were then washed with 5 x 1 ml buffer A,


92
suctioned to near dryness, and then transferred to scintillation vials.
Filtration was performed at 0-4C in a cold room. Radioactivity was
determined by liquid scintillation counting at 38% efficiency following
the addition of 1 ml H^O and 10 ml Triton-toluene scintillation cocktail
(toluene-Triton X-100, 2:1; 2, 5-diphenyloxazole, 4.375 g/1; dimethyl
POPOP, 43.75 mg/1) and disruption of the filters by vortexing of the
vials. Alternatively, the filters were dried overnight in a warm oven
and then counted at higher efficiency in a toluene based scintillation
cocktail not containing Triton X-100. The efficiency of the DEAE filter
assay was determined (as described below) by two different methods and
found to be 76%.
In order to calculate the efficiency of the DEAE filter assay some
of the binding data obtained with it were compared with those obtained
from the same samples with a Sephadex G-25 mini column gel filtration
assay and with a dextran-charcoal adsorption assay. In the former
procedure 50 yl aliquots of the sample were loaded onto Pasteur pi pet
mini columns filled with 1.5 ml Sephadex G-25 equilibrated in buffer A;
following collection of a 0.51 ml fraction that was discarded, a 0.8 ml
void volume containing bound radioactivity was collected and assayed by
liquid scintillation in a Triton-toluene cocktail. The dextran-charcoal
adsorption assay was performed by adding the 50 yl sample aliquot to a
1 ml suspension of dextran-coated charcoal (0.5% Norit A activated
charcoal, Fisher; 0.05% Dextran T-70, Pharmacia); following incubation
at 0-4C for 5 min with occasional vortexing the charcoal was pelleted
by centrifugation at 10,000 x g for 5 min. The supernatant was then
taken for the determination of bound radioactivity by liquid
scintillation counting.


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PAGE 330

81,9(56,7< 2) )/25,'$


UNIVERSITY OF FLORIDA
3 1262 08554 3261


MOUSE BRAIN GLUCOCORTICOID RECEPTORS
BY
HARRY E. GRAY
A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA

This dissertation is dedicated to the memory of
Clarence Phillips Connell

ACKNOWLEDGMENTS
I gratefully acknowledge the interest and support of my supervisory
committee: Drs. William G. Luttge, Robert J. Cohen, Adrian J. Dunn,
John B. Munson, and Don W. Walker.
I would also like to thank Elizabeth Webster and Dr. Neal Kramarcy
for assistance with the steroid radioimmunoassay, Dr. Richard Bonsall
for a particularly concise derivation of the solution to the rate
equation, Charles Densmore for assistance with animal surgery, and Nancy
Gildersleeve for assistance with computer programming and with a number
of biochemical techniques.
iii

TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS iii
ABSTRACT vi
CHAPTER
I.GENERAL INTRODUCTION 1
Biosynthesis, Secretion, and Metabolic
Effects of Glucocorticoids 1
Regulation of Glucocorticoid Secretion 5
Overview of Corticosteroid Mechanisms 9
Anatomical Distribution of Corticosteroid Binding .... 17
Characterization of Soluble Corticosteroid Receptors
in Brain 21
Physiological Regulation of Corticosteroid Receptors . . 27
Corticosterone "Membrane Effects" and Receptors 32
Summary 36
II.METHODS FOR THE DETERMINATION OF ASSOCIATION AND
DISSOCIATION RATE CONSTANTS AND FOR THE ESTIMATION OF
TIMES REQUIRED FOR THE ATTAINMENT OF ARBITRARY DEGREES
OF APPROACH TO EQUILIBRIUM BY NON-COOPERATIVE, SINGLE
SITE LIGAND-RECEPTOR SYSTEMS 39
Introduction 39
Theory 40
Applications and Discussion 44
III.LINEARIZATION OF THE TWO LIGAND-SINGLE BINDING SITE
SCATCHARD PLOT AND "EDâ„¢" COMPETITION DISPLACEMENT
PLOT: APPLICATION TO THE SIMPLIFIED GRAPHICAL
DETERMINATION OF EQUILIBRIUM CONSTANTS 55
Introduction 55
Theory and Application 57
Discussion 84
iv

Page
IV.EQUILIBRIUM BINDING CHARACTERISTICS AND HYDRODYNAMIC
PARAMETERS OF MOUSE BRAIN GLUCOCORTICOID BINDING SITES ... 86
Introduction 86
Materials and Methods 88
Results 109
Discussion 205
V.THE BINDING OF CORTICOSTERONE TO A CBG-LIKE COMPONENT
OF MOUSE BRAIN CYTOSOL 219
Introduction 219
Materials and Methods 225
Results 232
Discussion 257
VI.KINETIC STUDIES OF MOUSE BRAIN GLUCOCORTICOID
RECEPTORS 261
Introduction 261
Materials and Methods 264
Results 271
Discussion 292
VII.GENERAL DISCUSSION 297
BIBLIOGRAPHY 299
BIOGRAPHICAL SKETCH 319
v

Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
MOUSE BRAIN GLUCOCORTICOID RECEPTORS
By
Harry E. Gray
December 1982
Chairman: William G. Luttge
Major Department: Neuroscience
Glucocorticoid binding sites in cytosol prepared from whole brains
of female CD-I mice perfused 3-5 days after ovariectomy-adrenalectomy
were studied by equilibrium, kinetic and transport methods. In the
standard buffer (containing 10 mM Na^MoO^ and 2 mM dithiothreitol, DTT)
both unoccupied and occupied binding sites for [ Hjdexamethasone (DEX)
were stable at 2°C. The absence of DTT resulted in rapid loss of
unoccupied sites, and the absence of molybdate resulted in loss of
unoccupied sites with a t^ of 1 h at 12°C and 10 h at 2°C.
Equilibrium isotherms revealed one apparent class of saturable,
3 3
high-affinity binding sites (each) for [ H]DEX, [ Hjtriamcinolone
3
acetonide (TA), and [ Hjcorticosterone (B), but the concentration of
3 3
sites for [ H]DEX and [ H]TA (putative receptors) was only 63% of the
3
complete ensemble of [ H]B sites. The concentration of DEX-displaceable
3
[ H]B sites was equivalent to the receptor concentration measured with
vi

[3H]DEX and [3H]TA. DEX failed to interact with 37% of the [3H]B sites;
these sites resembled corticosterone binding globulin (CBG). The
(decreasing) order of steroid affinity for the putative receptors
measured with the [3H]1igands was: L3H]TA > [3H]DEX > [3H]B. The
competing steroids that were tested fell into the following order of
decreasing affinity (increasing Kdi) for the [ H]dexamethasone binding
sites: DEX > B > 11-deoxycorticosterone > progesterone % cortisol >
aldosterone > cortexolone > testosterone.
3 3
Measured rate constants for the association of [ H]DEX, [ H]TA, and
3
[ H]B with the receptors were very similar. The very different
affinities of these agonist ligands resulted from their quite different
dissociation rate constants. Progesterone at concentrations greater
than 10~6 M (but not DEX itself) significantly accelerated dissociation
3
of the L H]DEX-receptor complexes.
3
Nonactivated [ H]TA-receptor complexes possessed Stokes radius
o
77 A, sedimentation coefficient 9.7 S, and molecular weight 315,000
3
dal tons; heat-activated [ H]TA-receptor complexes (confirmed by
O
DNA-cellulose binding) possessed Stokes radius 58 A, sedimentation
coefficient 3.7 S, and molecular weight 90,000 daltons. Physical
o
characteristics of the cytosol CBG-like binder (Stokes radius 46 A,
sedimentation coefficient 4.1 S, molecular weight 70,000 daltons) were
indistinguishable from those of plasma CBG.
VI 1

CHAPTER I
GENERAL INTRODUCTION
Biosynthesis, Secretion, and Metabolic
Effects of Glucocorticoids
The adrenal cortex produces over forty steroids, but only a few of
these are secreted in biologically significant quantities. The major
active secretions are classified as glucocorticoids (e.g., cortisol,
corticosterone, 11-deoxycortisol) or mineralocorticoids (e.g.,
aldosterone, deoxycorticosterone), with 21 carbon atoms, and weak
androgens (e.g., dehydroepiandrosterone), with 19 carbon atoms (see
Table 1-1). Minor amounts of progestational and estrogenic steriods are
also secreted. The predominant glucocorticoid is cortisol in some
species, e.g., hamster, sheep, and primates, but it is corticosterone in
others, e.g., rat, mouse, and rabbit (Seth, 1969). Although cortisol is
the predominant circulating glucocorticoid in primates, corticosterone
may comprise a significant or even major fraction of the glucocorticoid
bound in brain cell nuclei (Turner, Smith and Carroll, 1979).
The enzymatic pathways for the synthesis of adrenal steroids from
cholesterol, which the adrenals may take up from blood or synthesize
from acetate, are well known (e.g., Fregly and Luttge, 1982). Briefly,
cholesterol undergoes a series of hydroxylations, catalyzed by the mito¬
chondrial desmol ase enzyme complex, leading to pregnenolone, which is
then converted to progesterone by the actions of the microsomal enzymes
1

Table 1-1: Adrenal steroid hormone names and abbreviations
IUPAC Names
Abbreviations
4-Androsten-17g-ol-3-one
5-Androsten-3g-ol -17-one
4-Pregnen-3, 20-dione
4-Pregnen-lla, 17a, 21-triol-3, 20-dione
4-Pregnen-llB, 17a, 21-triol-3,20-dione
4-Pregnen-l1e,21-diol-3,20-dione
4-Pregnen-l18,21-diol-3,18,20-trione
4-Pregnen-l7a-ol-3,20-dione
4-Pregnen-l7a,21-diol-3,20-dione
4-Pregnen-21-ol-3,20-dione
5-Pregnen-3B-ol-20-one
1.4-Pregnadien-9-fluoro-llB,16a,17a,
21-tetrol-3,20-dione 16, 17-acetonide
1.4-Pregnadien-9-f1uoro-16a-methyl-113,
17a,21-triol-3,20-dione
T
DHEA
P4
lla-F
F
B
Aldo
17a-0H-P4
DOF, S
DOC, 11-DOC
Pg
TA
DEX
Trivial Names
Testosterone
Dehydroepiandrosterone
Progesterone
Epicortisol
Cortisol
Corticosterone
Aldosterone
17a-Hydroxyprogesterone
Cortexolone
Desoxycorticosterone
Pregnenolone
Triamcinolone Acetonide
Dexamethasone

3B-hydroxy steroid dehydrogenase and 3-ketosteroid isomerase. Some
progesterone is converted to 17a-0H-progesterone by the cytoplasmic 17
a-hydroxylase. Progesterone and 17a-0H-progesterone are converted by a
cytoplasmic C-21 hydroxylase to 11-deoxycorticosterone and 11-deoxy-
cortisol, respectively. A mitochondrial lie- hydroxylase enzyme finally
converts 11-deoxycorticosterone and 11-deoxycortisol to the finished
glucocorticoid products corticosterone and cortisol. The adrenal cortex
does not store its secretions, but it does store an abundance of the
precursor cholesterol in lipid droplets. The adrenal stimulators
adrenocorticotropic hormone (ACTH) and angiotensin II, by processes
involving cyclic AMP, accelerate the conversion of cholesterol to
pregnenolone, the rate-limiting step in adrenal steroidogenesis. This
conversion is rapidly followed by the synthesis and secretion into the
circulation of the active corticosteroids.
Glucocorticoids are so named for their role in regulating glucose
metabolism. They act directly on most tissues, and indirectly influence
all tissues. An early effect of glucocorticoids is the inhibition of
glucose uptake by adipose tissue, skin, fibroblasts, and lymphoid
tissue. There is a decrease in macromolecular (protein, lipid, and
nucleic acid) synthesis and an increase in protein degradation in these
tissues and in muscle. There is an increase in lipolysis in fat cells,
and a depletion of glycogen in muscle. These catabolic actions result
in the release of amino acids, free fatty acids, glycerol, and
nucleotides into the circulation. In contrast, the actions of
glucocorticoids in the liver are primarily anabolic, resulting in a
general increase in RNA and protein synthesis, as well as the specific

4
induction of a number of enzymes. The amino acids derived from
peripheral catabclism are substrates for increased glucose formation
(gluconeogenesis) in liver, and to a lesser extent in the kidney.
Glycogen accumulates in liver, and blood glucose levels tend to rise.
The latter change induces a compensatory increase in insulin, which
counteracts many of the glucocorticoid effects.
Certain tissues are spared from the catabolic actions of
glucocorticoids - brain, red blood cells, heart, liver, kidney. These
tissues, perhaps more essential than others, may rather enjoy the
additional circulating glucose diverted from elsewhere or produced by
gluconeogenesis. The diverse actions of glucocorticoids may thus make
teleological sense as a coordinated mechanism for making glucose
maximally available to certain essential tissues during and immediately
following periods of environmental challenge or stress.
Glucocorticoids also have many diverse effects not related to
glucose metabolism. They act at multiple sites to suppress inflammatory
and allergic reactions, including inhibition of extravasation and
migration of leucocytes, edema, and phagocytosis, decrease in the
circulating lymphocytes and eosinophils, involution of the thymus, lymph
nodes and spleen, and decrease in antibody production. The lungs
respond to glucocorticoids with enhanced catecholamine sensitivity,
bronchodilation, and decreased vascular resistance. There may be
anabolic effects in the development of some organs, for example the
induction of surfactant secretion in the fetal lung. Glucocorticoid
actions have been reviewed comprehensively by Baxter and Rousseau
(1979). The effects of corticosteroids on the nervous system and

5
behavior have also been reviewed recently (Bohus, de Kloet and Veldhuis,
1982; Rees and Gray, 1983).
Regulation of Glucocorticoid Secretion
Glucocorticoids are released from the adrenals in response to ACTH,
which is in turn secreted by cells of the anterior pituitary in response
to corticotropin releasing hormone (CRH), of hypothalamic and perhaps
extrahypothalamic origin (Sayers and Portanova, 1975; Vale, Spiess,
Rivier and Rivier, 1981). Three factors are known to control
glucocorticoid secretion: stress, rhythms, and corticosteroid feedback.
The pituitary-adrenal system responds within a few minutes to a
wide variety of noxious stimuli, termed stressors. The "general
adaptation syndrome" (Selye, 1950) produced by this pituitary-adrenal
stress response is both nonspecific with respect to a variety of stimuli
and relatively slow to develop, in contrast to the autonomic responses
which can produce relatively stimulus-specific and extremely rapid
adaptive changes in many organ systems. Although a distinction is
frequently drawn between "physiological" stressors (e.g., trauma,
hemorrhage, hypoxia, infection, ether, cold, heat, fasting), and less
noxious "psychological" stressors (e.g., immobilization, handling, mild
electric shock, loud noise, and situations that produce fear, guilt,
anxiety, or frustration), this distinction is often blurred in practice.
When pain, discomfort, and emotional reactions were avoided carefully,
several "physiological stressors" (fasting, heat, exercise) no longer
elevated corticosteroid levels. This finding led Mason (1971) to
suggest that the essential property of all stressors may be the ability
to elicit a behavioral response of emotional arousal or hyperalerting,

6
which prepares the organism for flight, struggle, or strenuous exertion
in a threatening situation.
The circadian rhythm in glucocorticoid secretion appears to be
entrained by the organism's rest-activity cycle. The secretory peak
occurs just before the active phase, even when the relation of activity
to the lighting cycle is reversed, as in humans working on night shifts,
or in rats fed only during the day (e.g., Morimoto, Arisue and Yamamura,
1977). In addition to the circadian rhythm, higher frequency
oscillations in corticosteroid secretion have been revealed by frequent
sampling (every 20 minutes). Recent evidence (Holaday, Martinez and
Natelson, 1977) has shown that this pulsatile secretion, previously
regarded as "episodic," actually follows an ultradian rhythm (frequency
greater than one cycle in 24 hours), having a predominant periodicity of
about 90 minutes and other components harmonically related to the
circadian rhythm. These rhythmic fluctuations in plasma cortisol were
synchronized among 8 isolated, restrained, undisturbed monkeys,
indicating their entrainment by environmental factors such as the
feeding or lighting schedule. The unexpected finding that ultradian
cortisol rhythms were not disrupted by infusion of supramaximal ACTH
challenges the classic concept that periodic bursts of corticosteroid
output depend entirely on the immediately preceding release of ACTH.
The physiological function of corticosteroid rhythms is unknown.
ACTH secretion is regulated by two temporally distinct negative
feedback mechanisms, a rate-sensitive fast feedback (FFB), which occurs
5 to 30 minutes after steroid administration, and a proportional,
delayed feedback (DFB), which appears after one or more hours (Dallman
and Yates, 1969; Jones, Hillhouse and Burden, 1977). These two phases

7
are separated by a "silent" period, during which negative feedback is
not observed. Differences in the steroid structure-activity
relationships for FFB and DFB indicate that different receptor
mechanisms may be involved.
There is evidence that corticosteroid feedback actions may be
exerted at multiple sites. The sensitivity of ACTH-secreting pituitary
cells to inhibition by physiological doses of natural and synthetic
corticosteroids has been established clearly by studies in which the
possibility of hypothalamic involvement was circumvented and by studies
of pituitary cells in vitro (Kendall, 1971; Jones et al., 1977).
Hypothalamic tissue in vitro also showed a FFB effect of corticosterone,
due to decreased release of CRH (Jones et al., 1977). A series of
studies (e.g., Feldman and Conforti, 1980) demonstrated that posterior
hypothalamic deafferentation, dorsal fornix section, or dorsal hippo¬
campectomy reduced the inhibitory DFB effect of the synthetic
fluorinated glucocorticoid, dexamethasone on both basal and ether
stress-induced corticosterone secretion in the rat. These findings
suggest that the dorsal hippocampus also participates in the feedback
regulation of pituitary-adrenal function. Furthermore, several studies
(e.g., Carsia and Malamed, 1979) have indicated a direct inhibitory
effect of corticosterone and cortisol on ACTH-induced corticoster-
oidogenesis, suggesting that the self-suppression of adrenocortical
cells by end products may provide an additional fine adjustment of
steroidogenesis. What remains to be determined is the relative
physiological importance of glucocorticoid feedback at the various
sites--anterior pituitary, hypothalamus, extrahypothalamic structures,
and the adrenal cortex itself. Although it appears that dexamethasone

8
may act primarily at the pituitary level (Sakakura, Yoshioka, Kobayashi
and Takebe, 1981), the pituitary may be less responsive to natural
glucocorticoids. One explanation for this difference is that anterior
pituitary cytosol contains a transcortin-1ike macromolecule, which like
plasma transcortin binds corticosterone but not dexamethasone and has
negligible affinity for DNA-associated acceptor sites in the nucleus
(Koch, Lutz, Briaud and Mialhe, 1976). Thus, while the transcortin-1ike
binders cannot interfere with the action of dexamethasone, they can, by
competing with the "true" cytoplasmic glucocorticoid receptors, reduce
the amount of corticosterone able to interact with these receptors.
Such a mechanism might insure that under non-stress conditions the
pituitary glucocorticoid receptors would not be occupied, thus allowing
them to function only in response to much higher, stress-induced levels
of corticosterone.
Glucocorticoids may also act directly upon the hypothalamus and
pituitary to modulate the production or secretion of hormones other than
CRH and ACTH, such as TRH, TSH, and GH (e.g., Burger and Patel, 1977).
The "compensatory" hypertrophy of the remaining adrenal following
unilateral adrenalectomy was long considered a result of decreased
corticosteroid feedback. However, compensatory adrenal growth was
recently shown to be neurally rather than hormonally mediated, dependent
on reciprocal neural connections between the hypothalamus and adrenal
(Dallman, Engeland and Shinsako, 1976).
While much progress has been made in elucidating individual factors
influencing pituitary-adrenal activity (neural input, feedback, stress,
rhythms), there is still a significant gap in our understanding of how
these isolated components function together in the intact organism.

9
Overview of Corticosteroid Mechanisms
Many of the effects of corticosteroids are believed to be mediated
by interactions of the steroid molecules with steroid-specific
cytoplasmic macromolecular receptors which concentrate as hormone-
receptor complexes in the target cell nuclei, where they initiate the
alterations in specific RNA and protein metabolism that then lead to the
ultimate physiological, neuroendocrine and behavioral effects. Other
less well-understood steroid effects may result from direct interactions
of the steroid molecule with components of target cell membranes. Some
established and hypothetical events in corticosteroid action are
represented in Fig. 1-1.
Although the natural adrenal steroids are soluble enough to be
transported unassisted in plasma, about 75% of the circulating
glucocorticoid (cortisol or corticosterone) is bound to an a-globulin
called transcortin or corticosteroid-binding globulin (CBG), about 15%
is bound to serum albumin, and only about 10% is free (Westphal, 1975).
Plasma transcortin does not seem to be necessary in any way for the
biological activity of the steroids; current evidence supports the dogma
that only the free steroid in the plasma can exert physiological action.
Although the brain capillary transit time is too short in relation to
the dissociation rate or half-life (t^) of the CBG-glucocorticoid
complex to allow the uptake of CBG-bound cortisol and corticosterone,
the albumin-bound corticosteroids dissociate rapidly enough to be
available for transport through the blood-brain barrier (Pardridge,
1981). (Liver capillary transit time and membrane permeability are

Fig. 1-1. Some established and hypothetical steps in corticosteriod action. S =
molecule, R = receptor, APO-R = aporeceptor.
Different shapes of R represent different conformations or covalent modifications
broken lines indicate hypothetical mechanisms or loci of hormone action.
steroid
The

ACIDS TRANSMITTERS ETC.

12
greater, allowing uptake of both albumin and CBG-bound glucocorticoids.)
Transcortin does reduce the amplitude of free glucocorticoid variations
in response to large rhythmic or stress-induced changes in adrenal
output. The potent synthetic fluorinated glucocorticoids (dexamethasone
and triamcinolone), as well as the natural mineralocorticoid
aldosterone, are only very weakly bound by transcortin. Since the
natural glucocorticoids can significantly occupy mineralocorticoid
receptors when present in high concentrations, and since the total
concentration of plasma glucocorticoids is much greater than the normal
concentration of aldosterone, the "buffering" effect of glucocorticoid
binding by transcortin is apparently necessary to prevent the saturation
of mineralocorticoid receptors by glucocorticoids (Funder, Feldman and
Edelman 1973). It is not known why the glucocorticoid/mineralocorticoid
ratio is so large, requiring this rather peculiar mechanism to confer
specificity of hormone action.
It is often assumed that target cell membranes do not present a
barrier to free lipophilic steroids, and that their passage into the
target cell is governed solely by simple diffusion. Recent studies
have, however, demonstrated for at least several different cell types
(isolated rat liver and pituitary cells and ACTH-secreting mouse
pituitary tumor cells) that glucocorticoid passage through the plasma
membrane may involve carrier-mediated transport in addition to simple
diffusion (e.g., Harrison, Fairfield and Orth, 1977; Koch, Sakly and
Lutz-Bucher, 1981). It is not yet clear how general this phenomenon may
be in terms of other target cells and hormones.

13
It has been observed that some steroids may have several different
actions in the nervous system that are mediated independently by their
different metabolites, but there is no evidence that the metabolites of
the natural glucocorticoids corticosterone and cortisol are functionally
important and possess their own non-enzymatic high-affinity binding
sites in brain or pituitary. Following in vivo injections of
[ Hjcorticosterone the radioactivity extracted with methylene chloride
from the nuclear fraction of rat brain was found to consist of
approximately 90% authentic (isochromatographic) corticosterone (McEwen,
Magnus and Wallach, 1972). Further investigation of glucocorticoid
metabolism in brain tissue is required, however, since acid metabolites
of cortisol possessing different, specific biological activities (as
enzyme inducers) have recently been found in rat liver (Voigt and
Sekeris, 1980).
The cytoplasmic steroid receptors are thermolabile proteins with
stereo-specific binding sites. Before the steroid can bind to the
-9
receptor with high affinity (K^ * 10 M), the corticosteroid receptor
protein ("aporeceptor") may be required to undergo an energy-
dependent transformation (possibly a phosphorylation) in order that the
potential binding site may be "switched on" to the appropriate
conformation for interaction with the steroid. A rapid "switching-off"
or down-regulation of the steroid-binding sites (possibly mediated by a
phosphatase) has also been observed, suggesting that cells may utilize
an internal phosphorylation-dephosphorylation feedback cycle to modulate
physiological responses by regulating the amount of receptor capable of
interacting with free steroid. Thus, under many circumstances a
substantial pool of latent or "cryptic" aporeceptors may be present in

14
many target cells. This dynamic regulation of the hormone binding site
itself has only recently been explored in cells derived from a few
peripheral tissues (e.g., Sando, Hammond, Stratford and Pratt, 1979),
and is an intriguing area for brain studies (e.g., Luttge, Densmore and
Gray, 1982). The number of receptors capable of interacting with free
steroid may be subject to additional regulation by certain proteolytic
enzymes that can disconnect the steroid binding site from the region of
the receptor molecule that contains the nuclear binding site, resulting
in non-functional steroid-binding fragments termed "mero-receptors"
(e.g., Niu, Neal, Pierce and Sherman, 1981).
After binding, the non-covalent cytoplasmic steroid-receptor
complex must next undergo a transformation that results in the
development of a high affinity for certain nuclear components associated
with the genome. This process of "activation" probably involves a
steroid-induced conformational change in the acidic receptor protein
which brings a positively-charged "acceptor" binding site to the surface
of the molecule (e.g., Barnett, Schmidt and Litwack, 1980). The nuclear
"acceptors" to which the activated receptor complexes now bind are
unidentified components of chromatin (possibly non-histone proteins)
that possess high-affinity and, to varying extents, tissue- and
receptor-specific binding domains. Although the acceptors are probably
not merely specific DNA nucleotide sequences, they do appear to regulate
the interactions of the steroid-receptor complexes with the DNA (e.g.,
Bugany and Beato, 1977; Cidlowski and Munck, 1980).
Following the formation of the ternary steroid-receptor-acceptor
complex the chromatin structure becomes altered in subtle ways that lead
to changes in the rates of transcription of specific mRNA species (e.g.,

15
Johnson, Lan and Baxter, 1979). These specific mRNA molecules are then
translated to produce the proteins that mediate the hormone-induced
physiological responses. Fig. 1-1 indicates that the proteins whose
rates of synthesis are modulated by the steroid may encompass a broad
spectrum of cellular functions: additional steroid receptors;
components or modulators of membrane transport mechanisms; enzymes of
intermediary metabolism; protein kinases, components of peptide hormone-
or neurotransmitter-sensitive receptor-adenylate cyclase complexes, and
other modulators whose altered synthesis may contribute to the so-called
"permissive" effects of steroids; and even specific proteins required
for some catabolic steroid effects (e.g., thymus involution) are all
examples of proteins that may be regulated to produce the ultimate
steroid response (e.g., Baxter and Rousseau, 1979).
After exerting their genomic effect, the receptors are either
degraded or recycled back to their unbound, nonactivated cytoplasmic
form by a process that may be linked to cell metabolism by a requirement
for ATP (e.g., Aronow, 1978). The nuclear "processing" of the
receptors, the "off-reaction," and receptor recycling are understood
very poorly; it is possible that some steroid dissociation may occur
before the receptors are released from their chromatin acceptor sites,
and there are hints that the process may be coupled to the proposed
cyclic transformations of the steroid binding sites. The released
steroid molecules may either re-enter the receptor cycle or diffuse out
of the cell into the circulation to enter another cell or to be
metabolized and excreted.
Fig. 1-1 also indicates several largely unexplored potential
mechanisms of steroid influence on cellular function that do not

16
directly involve events at the genome. The suggestions that
corticosteroid-receptor complexes may directly exert translational
(e.g., Kulkarni, Netrawali, Pradhan and Sreenivasan, 1976) or
post-translational (e.g., Trajkovic, Ribarac-Stepic and Kanazir, 1974)
control over specific protein synthesis or that they may directly
regulate membrane transport mechanisms are hypothetical at present. The
suggestion that some glucocorticoid effects may result from the
interaction of free steroids with intracellular membrane systems is also
hypothetical (for review, see Nelson, 1980); glucocorticoids are known
to modify some membrane properties, but no functional consequences of
such changes are yet well established. Free steroids may also exert
important effects at the cell plasma membrane; these include rapid,
steroid-specific changes in the firing rates of some neurons (for
review, see Feldman, 1981; McEwen, David, Parsons and Pfaff, 1979).
Since a steroid's affinity for the cytoplasmic receptors does not
adequately predict the magnitude of the physiological response, it is
necessary to classify all steroids into one of four categories on the
basis of their physiological effectiveness (Rousseau, Baxter and
Tomkins, 1972). Optimal inducers are steroids that all produce the same
maximal response when present in saturating amounts. For example,
aldosterone will produce as great a glucocorticoid response as
dexamethasone (in many tissues) when present in very high concen¬
trations. Suboptimal inducers elicit smaller, less-than-maximal
responses even when present in saturating concentrations; 11-deoxy¬
corticosterone is an example of a suboptimal glucocorticoid. Anti¬
inducers or antihormones produce no typical physiological responses by
themselves, but rather behave as competitive inhibitors of the active

17
hormones; progesterone and cortexolone (11-deoxycortisol) are
antiglucocorticoids. Finally, inactive steroids do not bind to the
specific steroid receptors at all. It should be stressed that the
classification of a particular steroid must refer to a specific,
measurable response and may vary among species and from one tissue to
another.
It is believed that different ligands can promote different degrees
of conformational change, leading to the formation of steroid-receptor
complexes with different states of "partial activation" (different
affinities for nuclear acceptor components). Munck and Leung (1977)
have proposed that each relevant steroid or class of steroids binds to
the receptor and promotes a subsequent conformational change that
differs in degree from that produced by other steroids. Optimal
inducers produce the highest degrees of activation, and anti-inducers
either do not promote activation or promote minimal, ineffective
increases in affinity for nuclear acceptors. Suboptimal inducers
produce intermediate states of activation. Other models of agonist and
antagonist interactions with the glucocorticoid receptor are also under
active consideration (Rousseau and Baxter, 1979; Sherman 1979).
Anatomical Distribution of Corticosteroid Binding
3
Neuronal nuclear concentration of [ Hjcorticosterone has been
demonstrated by autoradiography in structures of the limbic system,
brain stem, and spinal cord, but not in the hypothalamus (McEwen,
Gerlach and Micco, 1975; Stumpf and Sar, 1975; Warembourg, 1973). In
3
adrenalectomized rats, nuclear accumulation of [ H]corticosterone was
most intense in structures related to the hippocampus, including the

18
postcommissural hippocampus, dentate gyrus, induseum griseum
(supracallosal hippocampus), anterior (precommissural) hippocampus, and
subiculum. Strong nuclear labeling was also seen in the lateral septum,
amygdala (cortical, central, and basomedial nuclei), and the piriform,
entorhinal, suprarhinal, and cingulate cortices. Additional labeling,
although weaker and less frequent, was present in the anterior olfactory
nucleus, medial amygdaloid nucleus, habenula, red nucleus, and
subfornical organ. Motor neurons in cranial nerve nuclei and spinal
cord were strongly labeled, and some glial cells were weakly labeled
(Stumpf and Sar, 1979). The pattern of in vivo uptake of [ H]cor-
ticosterone determined by autoradiography (highest in hippocampus and
septum, followed by amygdala, cortex and hypothalamus) agrees well with
the anatomical distribution of cytoplasmic [ Hjcorticosterone binding
sites (McEwen et al., 1972; Grosser, Stevens and Reed, 1973); and with
3
the patterns of [ Hjcorticosterone binding found in purified nuclei both
o
following [ Hjhormone injections in vivo (McEwen, Weiss and Schwartz,
1970) and after incubation of brain slices with [ Hjcorticosterone in
vitro (McEwen and Wallach, 1973; de Kloet, Wallach and McEwen, 1975).
Corticosterone target cells have been observed in the anterior pituitary
of the rat (Warembourg, 1973) and Pekin duck (Rhees, Abel and Haack,
1972), but not the rhesus monkey (Pfaff, Gerlach, McEwen, Ferin, Carmel
and Zimmerman, 1976).
3
The distribution of target cells for [ Hjcortisol in the brains of
adrenalectomized rats was identical to that for [ Hjcorticosterone
(Stumpf and Sar, 1973). Nuclear binding sites for cortisol appeared to
be saturated by endogenous corticosteroids in adrenally intact mice
(Schwartz, Tator and Hoffman, 1972) and guinea pigs (Warembourg, 1973).

19
The synthetic glucocorticoid dexamethasone displayed a surprisingly
different pattern of uptake from that of natural glucocorticoids.
Whereas corticosterone and cortisol were concentrated strongly by
neurons, [ H]dexamethasone was accumulated weakly by all types of cells
in the brain (Rees, Stumpf and Sar, 1975; Rhees, Grosser and Stevens,
1975). The labeling was heaviest in epithelial cells of the choroid
plexus and ventricular lumen, and was also observed in vascular
endothelial cells, glia, meninges, ependyma, circumventricular organs,
and in neurons in areas near the third ventricle (preoptic area,
hypothalamus, thalamus) and lateral ventricle (septum, caudate,
amygdala). In contrast to [ Hjcorticosterone, [ Hjdexamethasone was
concentrated only very weakly by hippocampal neurons. Furthermore, the
presence of endogenous adrenal hormones in intact rats did not affect
the pattern of [ Hjdexamethasone localization (Rhees et al., 1975). In
the pituitary, dexamethasone was concentrated heavily by cells in the
pars distal is (particularly corticotrophs) and pars nervosa, but not
pars intermedia (Rees, Stumpf, Sar and Petrusz, 1977). The autoradio¬
graphic data were consistent with the pattern of in vivo uptake of
3
[ Hjdexamethasone revealed by direct measurements of tissue radio¬
activity (de Kloet, van der Vies, and de Wied, 1974).
The strikingly different patterns of distribution of these natural
and synthetic glucocorticoids have been interpreted as evidence for the
existence of at least two classes of glucocorticoid receptors differing
in their distribution and steroid specificity. However, some of the
findings may be explained without reference to the concept of receptor
heterogeneity. There are large differences in the permeability of the

20
blood-brain barrier to different steroids (Pardridge and Mietus, 1979).
Dexamethasone appears to enter the brain more slowly than corti¬
costerone; time course studies showed that maximal binding in hippo¬
campal cell nuclei occurred one hour after injection of
3 3
[ Hjcorticosterone, but two hours after [ H]dexamethasone (de Kloet et
3
al., 1975). Similarly, the cellular accumulation of [ Hjdexamethasone
in the hippocampus seen autoradiographically three hours after injection
was not yet evident at 30 minutes (Rees et al., 1975). The greater
blood-brain barrier to dexamethasone may also explain some discrepancies
between the patterns of nuclear binding of glucocorticoids obtained in
vivo and in slices incubated in vitro. Although the in vivo nuclear
binding of [ Hjcorticosterone in hippocampus was more than ten times
that of [ Hjdexamethasone, this difference was dramatically reduced
(corticosterone: dexamethasone ratio of 1.2 - 1.5) when slices of
hippocampus were incubated with the steroids in vitro (de Kloet et al.,
1975; McEwen, de Kloet and Wallach, 1976). It is possible that the
small but significant remaining differences in nuclear binding observed
in the in vitro slice experiments (i.e. greater binding of corti¬
costerone in hippocampus and of dexamethasone in hypothalamus and
pituitary) may have resulted from factors other than glucocorticoid
receptor heterogeneity: for example, differences in the rates of
cellular penetration of the two steroids which may persist in the slice
experiments, and differences in the relative abilities of the two
steroids to promote activation and nuclear binding of the steroid-
receptor complexes (e.g., Svec and Harrison, 1979).

21
Characterization of Soluble Corticosteroid
Receptors in Brain
The natural glucocorticoids, corticosterone and cortisol; the
synthetic glucocorticoids triamcinolone acetonide (TA) and
dexamethasone; and the natural mineralocorticoids, aldosterone and
11-deoxycorticosterone (DOC), bind to steroid-specific, saturable brain
cytosol components believed to be the physiological transducer molecules
or "receptors." One goal of receptor research is to identify the
different classes or categories of adrenal steroid action in the brain
and to study individually the receptors mediating these actions. The
categories "glucocorticoid" and "mineralocorticoid" are defined by
distinguishable peripheral physiological effects and steroid specific¬
ities; this distinction may be meaningful in the nervous system, but it
should not be assumed a priori that brain steroid effects and speci¬
ficities closely correspond to those of other organ systems.
In comparison with the corticosteroid receptors found in other
tissues, the few reported physicochemical properties of brain receptors
are generally unremarkable. They have been distinguished from those of
transcortin by a number of criteria; unlike transcortin, the brain
cytoplasmic glucocorticoid binding protein was found to bind the
synthetic steroids dexamethasone and TA with high affinity and to
possess sulfhydryl groups whose modification led to the loss of
functional steroid binding sites (e.g., Chytil and Toft, 1972; McEwen
and Wallach, 1973).
The resolution of the different classes of brain corticosteroid
receptors is confusing because it involves two distinct but related
issues: the possible existence of separate binding sites for natural
and synthetic glucocorticoids; and the distinction between

22
glucocorticoid and mineralocorticoid binding sites. The principal
technique for defining distinct binding sites is the in vitro
measurement of steroid specificity in competition experiments. Oddly,
the actual affinities of different competing steroids for brain cytosol
3
[ H]steroid binding sites have seldom been reported. Specificity data
have typically been reported only as a rank ordering of the abilities of
different steroids to compete for the binding of a given [ H]steroid.
Although both natural and synthetic agonists were bound with
similar high affinities by brain cytosol (Chytil and Toft, 1972),
dexamethasone did not reduce the binding of [ H]corticosterone in whole
brain cytosol to the extent that was predicted from its physiological
potency as a peripheral glucocorticoid (Grosser et al., 1973; McEwen and
Wallach, 1973). In most studies, corticosterone and dexamethasone were
3 3
equally effective in competition for [ Hjdexamethasone and [ H]TA
binding (e.g., Chytil and Toft, 1972; Stevens, Reed and Grosser, 1975;
de Kloet and McEwen, 1976).
Comparative measurements of the total cytosol binding capacity for
corticosterone and dexamethasone have been reported. Because a number
of poorly understood variables (such as the composition of the
incubation buffer, the presence or absence of phosphatase inhibitors,
the time elapsed between tissue homogenization and cytosol labeling with
3
[ H]steroid, etc.) have not yet been fully explored or controlled,
published estimates of apparent binding capacity (Bm 1 are often in
max
conflict. The discovery by de Kloet et al. (1975) that the spontaneous
3
loss of [ H]dexamethasone binding capacity from unlabeled cytosol was
3
more rapid than the loss of [ H]corticosterone binding sites, stimulated
experiments in which tissues were homogenized in the presence of the

23
3
[ H]steroids. With this alteration in methodology, binding capacities
3 3
for [ H]dexamethasone and [ H]corticosterone in hippocampal cytosol were
found to be equal, and hypothalamic cytosol had an even slightly higher
capacity for [ H]dexamethasone than for [ Hjcorticosterone (e.g., de
Kloet et al., 1975; Turner and McEwen, 1980).
High affinity mineralocorticoid (type I) binding sites, which occur
in significant concentrations principally in the hippocampus and
associated structures, have been studied in rat brain cytosol (Anderson
and Fanestil, 1976; Moguilewsky and Raynaud, 1980). The mineralo¬
corticoid receptors have high affinity for aldosterone and DOC and,
surprisingly, an almost equally high affinity for progesterone. Since
[ Hjaldosterone, [ H]corticosterone and [ Hjdexamethasone all bind (with
different affinities) to both glucocorticoid and mineralocorticoid brain
receptor sites, it has been most productive to study the binding of
[ Hjaldosterone in the presence of an excess of the "pure" gluco¬
corticoid R26988 (Moguilewsky and Raynaud, 1980). Although concen¬
trations of glucocorticoid and mineralocorticoid receptor sites were
comparable in hippocampal cytosol, the concentration of high-affinity
mineralocorticoid binding sites was much lower than the concentration of
glucocorticoid binding sites in whole brain.
Although the discrepancies between in vivo and in vitro (brain
3 3
slice) nuclear binding of [ Hjcorticosterone and [ Hjdexamethasone can
be explained largely without reference to the possible heterogeneity of
unbound glucocorticoid receptors, several observations (such as the
relatively poor ability of dexamethasone to compete for [ Hjcorti¬
costerone binding sites) have suggested that natural and synthetic
glucocorticoids may bind to somewhat different receptor populations.

24
When cytosol samples were chromatographed on DEAE-cellulose ion-exchange
3 3
columns, complexes formed with [ H]corticosterone and [ Hjdexamethasone
3
were eluted as multiple peaks, and the proportion of bound [ Hjsteroid
in each of the two major peaks differed for the two glucocorticoids (de
Kloet and McEwen, 1976). Although it is unlikely that the two major
peaks of both hippocampal [ Hjdexamethasone and [ Hjcorticosterone
binding merely represent different pools of activated and nonactivated
receptors, it is quite possible that they are distinct proteolytic
fragments (created in vitro) of a single larger intact glucocorticoid
receptor. Affinity chromatography of rat brain cytosol on columns of
immobilized deoxycorticosterone (DOC) hemisuccinate (subsequently eluted
3
with [ Hjcorticosterone) selectively purified one of the two major
3
[ Hjcorticosterone binding peaks resolved by ion exchange chromatography
(de Kloet and Burbach, 1978).
Apparent receptor heterogeneity was also observed in rat brain (and
pituitary) cytosol following isoelectric focussing of labeled samples on
polyacrylamide gels (MacLusky, Turner and McEwen, 1977). In brain
cytosol three major specific [ Hjcorticosterone binding peaks were
resolved; these had isoelectric points (pis) of approximately 6.8, 5.9
and 4.3. When [ Hjdexamethasone was the ligand only two peaks were
found (the peak at pi 4.3 was absent). Furthermore, the relative sizes
of the two remaining peaks were different for the two ligands. Wrange
(1979) has suggested that the apparent receptor heterogeneity observed
by MacLusky et al. (1977) may have resulted from proteolytic artifacts
and that the brain cytosol [ Hjcortiscosterone binding peak at pi 4.3
(reported by the same workers) can probably be attributed to residual
transcortin (CBG) remaining in the tissue following incomplete

25
perfusion. Wrange found only a single peak of radioactivity (at pi 6.1)
when rats were extensively perfused and hippocampal cytosol samples
labeled with either [ Hjcorticosterone or [ Hjdexamethasone were
analyzed. However, it was not possible to conclude that CBG or a class
of CBG-like binding sites was definitely not present, since free steroid
was removed from the samples prior to the relatively long focussing
procedure, which would have both allowed extensive dissociation of
steroid from the CBG and eventually denatured the steroid binding sites
as they entered the region of low pH. Wrange also found that limited
tryptic digestion of hippocampal cytosol labelled with either
[ Hjcorticosterone or [ Hjdexamethasone produced two peaks of bound
radioactivity having pi values of 6.0 and 6.4. These pi values are
close enough to those reported by MacLusky et al. (1977) to suggest that
proteolytic fragments of a single molecule may have been responsible for
the observed heterogeneity. The relative sizes of the two trypsin-
induced peaks were different when [ Hjdexamethasone was substituted for
[ Hjcorticosterone; this situation may have resulted either from the
possession of slightly different trypsin substrate characteristics by
the receptor complexes formed with the different steroids or from
3
different rates of dissociation of [ Hjcorticosterone from the two
trypsin-induced receptor fragments.
The autoradiographic data reviewed above have led to the suggestion
that neurons contain glucocorticoid receptors that preferentially bind
corticosterone and cortisol, whereas glial cells contain glucocorticoid
receptors having higher affinity for dexamethasone and TA (e.g., McEwen
et al., 1979). There is, however, very little evidence to support this
dichotomy. Although dexamethasone is a potent inducer of glycerol-

26
phosphate dehydrogenase (GPDH) in cultured glial tumor cells, and
cytosol prepared from these tumor cells and from optic nerve
oligodendrocytes contains high-affinity [ Hjdexamethasone binding sites,
glial cells also respond to natural glucocorticoids (e.g., Breen,
McGinnis and de Veil is, 1978; Cotman, Scheff and Benardo, 1978).
Furthermore, there is no evidence (e.g., Clayton, Grosser and Stevens,
3
1977) that brain [ Hjdexamethasone binding capacity increases faster
3
than [ Hjcorticosterone binding capacity during the period of rapid
glial growth associated with myelination. Glial tumor cells were found
to contain only one glucocorticoid receptor with a pi of 5.9,
corresponding to the molecular species that bound [ Hjdexamethasone
preferentially in the rat brain (MacLusky, unpublished, cited by McEwen
et al., 1979). This observation cannot, however, be considered strong
evidence for a neuronal-glial receptor dichotomy, since Wrange (1979)
reported a similar isoelectric binding profile containing only a single
radioactive peak in hippocampal cytosol from perfused animals. It is
possible that different concentrations of proteolytic enzymes in the
cytosol samples prepared from brain tissue and from cultured glial cells
could explain the differences between the [ Hjglucocorticoid binding
profiles observed by MacLusky and colleagues in these different
preparations. The demonstration that [ Hjdexamethasone binding sites
disappear from hippocampal cytosol (in the absence of steroid) more
rapidly than [ Hjcorticosterone binding sites (de Kloet et al., 1975)
may result from the gradual alteration of a single initial population of
steroid binding sites by enzymatic processes that are triggered upon
cell disruption and that proceed rapidly in the absence of protective

27
steroid ligands. This apparent differential loss of free binding sites
for [ Hjdexamethasone and [ H]corticosterone may also result, at least
in part, from the presence of a population of relatively more stable CBG
or CBG-like binding sites in the hippocampal cytosol. Clarification of
this complex issue must await the purification and comparison of both
intact unbound receptors and steroid-receptor complexes.
Physiological Regulation of Corticosteroid Receptors
The ontogeny of the capacity of rat brain cytosol to bind both
natural and synthetic glucocorticoids has been studied. Binding of
[ Hjdexamethasone was very low immediately after birth, but it reached
3
the adult level sooner than [ H]corticosterone binding, which was higher
3
than that of [ H]dexamethasone immediately after birth. Adult levels of
3 3
[ H]corticosterone binding were similar to those of [ H]dexamethasone in
both hippocampal and hypothalamic cytosols (Olpe and McEwen, 1976).
Turner (1978) found that the amount of [ Hjcorticosterone bound by
hippocampal nuclei in adrenalectomized rat pups injected with steroid in
vivo was very small in comparison with adult levels. Furthermore, the
nuclear binding of [ Hjcorticosterone by hippocampal pyramidal and
dentate granule cells as determined by autoradiography was correlated
directly with neuronal age; in the neonatal hippocampus the oldest cells
revealed the heaviest labeling, whereas newly arrived cells showed
little nuclear retention of steroid. Thus, although the aporeceptor
proteins may appear much earlier in development, the production of
receptors with functional binding sites and the potential for activation
to the nucleophilic state may occur relatively late in the differ¬
entiation of these neurons.

28
An age-related decline in corticosterone receptors has been
reported in mouse hippocampus (Finch and Latham, 1974) and in rat
cerebral cortex (Roth, 1974). Evidence suggests that senescent
intracellular biochemical changes rather than cellular losses are
responsible for the decline in cortical receptors (Roth, 1976).
The concentration of intracellular corticosteroid binding sites
rises in response to steroid deprivation. Adrenalectomy caused a
two-stage increase in the nuclear binding of [ Hjcorticosterone by
hippocampus in vivo and in vitro (McEwen, Wallach and Magnus, 1974) and
increased glucocorticoid cytosol receptor concentrations (Stevens et
al., 1975; Olpe and McEwen, 1976). The apparent receptor content
increased rapidly for the first 2 hours after adrenalectomy and then
remained at a plateau for about 12 hrs; the second, slower increase
began between 12 and 18 hours after adrenalectomy and approached a new
plateau after about 3 days. The first, rapid change, which parallels
the decline in plasma corticosterone, certainly represents the
disappearance of endogenous corticosterone from brain binding sites and
may also reflect the "switching-on" of the steroid binding sites of
receptors. The interesting long-term increase results from either the
synthesis of new receptors on the "switching-on" of previously
unobservable "cryptic" aporeceptors.
Both the concentration of endogenous corticosteroids and the
occupancy of corticosteroid receptors in the brain vary with changes in
plasma steroid levels. Brain glucocorticoid concentrations, which were
intermediate between free and total plasma concentrations and therefore
possibly equal to the plasma glucocorticoid concentration available for
brain uptake (the free + albumin-bound or "BBB-transportable"

29
concentration) (Carroll, Heath, and Jarrett, 1975), were found to
fluctuate in parallel with both basal circadian and stress-induced
changes in the plasma steroid concentrations (Butte, Kakihana and Noble,
1976; Carroll et al., 1975). Furthermore, the diurnal and stress-
induced increases in plasma corticosterone decreased the in vitro
cytosol binding of [ H]corticosterone in all brain regions examined
(Stevens, Reed, Erickson and Grosser, 1973). In most brain regions of
unstressed animals, glucocorticoid receptor occupancy varies between
about 50% at the diurnal trough and approximately 80% at the peak
(Stevens et al., 1973; McEwen et al., 1974; Turner, Smith and Carroll,
1978a,b). In contrast to other brain regions, the preoptic and septal
areas exhibited a high level of receptor occupancy even during the
morning corticosterone minimum, and no increase at the evening peak
(Turner et al., 1978a,b). However, all brain regions showed a circadian
3
variation in the total concentration of cytosol [ H]corticosterone
3
binding sites. Furthermore, the same dose of [ H]corticosterone
injected into adrenalectomized mice produced higher hippocampal steroid
concentrations at different times of the day (Angelucci, Valeri,
Palmery, Patacchioli and Catalani, 1980). The peak brain concentra¬
tions varied as the normal circadian rhythm, suggesting that a
steroid-independent rhythm of receptor concentration may persist in the
adrenalectomized animals.
An investigation of the temporal relationship between
glucocorticoid nuclear binding and the availability of cytosol binding
sites led to the unexpected finding that there was no net depletion of
total hippocampal cytosol binding capacity as a result of nuclear
translocation 15-60 min after the injection of fully saturating doses of

30
3 3
either [ Hjcorticosterone or [ H]dexamethasone (Turner and McEwen,
1980). The predicted cytosol receptor depletion was based on
hippocampal nuclear uptake measured following the in vivo [ Hjsteroid
3
injections. Cytosol samples from rats injected with [ Hjsteroids were
3
incubated in vitro with additional [ Hjsteroids to determine the maximal
cytosol steroid binding capacity, but no depletion of this total
capacity as a result of nuclear translocation was ever observed. This
3
investigation also revealed that [ Hjcorticosterone injected in vivo
could occupy no more than 40% of the total cytosol binding sites
measured in vitro. These results suggest the existence of a reserve
pool of aporeceptors or "cryptic" receptors which can be rapidly
converted to the form capable of binding steroids. However, it must not
be assumed that these findings are characteristic only of brain tissue;
the same glucocorticoid injection produced large differences in
cytoplasmic receptor depletion among 6 different rat glucocorticoid
target tissues (Ichii, 1981). For example, an injection of
dexamethasone that depleted 75% of heart and muscle cytoplasmic
receptors depleted only 40% of liver and lung receptors and only 10% of
thymic and spleen receptors (brain samples were not included). Much
larger injections were able to fully deplete receptors in all 6 tissues.
Neuropeptide effects on functional steroid receptor concentra-
tions have been observed. The increase in [ Hjcorticosterone binding
capacity of rat hippocampal cytosol observed after hypophysectomy
combined with adrenalectomy was greater than that after adrenalectomy
alone. Both ACTH^ ^ (steroidogenic) and ACTH^ (devoid of
corticotrophic activity) eliminated the additional increase attributed
to hypophysectomy. Furthermore, vasopressin-deficient (Brattleboro

31
strain) rats were found to have abnormally low hippocampal cytosol
3
[ H]corticosterone receptor levels that could be restored by
9 8
physiological doses of vasopressin or des-glycinamide -arg -vasopressin
(a behaviorally potent analog having low antidiuretic activity) (de
Kloet and Veldhuis, 1980; de Kloet, Veldhuis and Bohus, 1980).
Several observations indicate the possibility of a rapid, dynamic
regulation of the availability of brain steroid binding sites.
Hippocampal electrical stimulation resulted in increased in vivo uptake
of [ H]cortisol into hypothalamic cells and an increase in the
proportion of intracellular hormone bound in the nucleus (Stith, Person
and Dana, 1976a). A single injection of reserpine into cats resulted
(at 16 hrs post injection) in a decreased concentration of cytosol
binding sites for [ Hjdexamethasone (Weingarten and Stith, 1978). A
rapid influence of metyrapone (an inhibitor of adrenal 116-hydroxylase)
on the binding of [ H] cortisol in pig hypothalamic slices incubated in
vitro at 37°C has also been reported (Stith, Person and Dana, 1976b).
3
The quantity of [ Hjcortisol bound to cytosol components after 30 min
3
was reduced by 50%, and nuclear-bound [ Hjcortisol was inhibited by 70%;
the mechanism of this inhibition is unknown.
Lesions have been used to explore possible influences of
hippocampal afferents and efferents on the concentration of hippocampal
glucocorticoid receptors. Transection of the fimbria bilaterally for a
duration of 6 or 80 days did not affect either the concentration of
3 3
hippocampal [ Hjcorticosterone and [ Hjdexamethasone receptors or the
increase in this concentration observed following adrenalectomy (Olpe
and McEwen, 1976). Furthermore, fimbria transection in 3-day-old rats
did not affect the normal ontogenetic increase in hippocampal binding

32
3 3
sites for [ H]dexamethasone and [ H]corticosterone. In contrast, the
3
concentration of hippocampal [ H]corticosterone receptors was elevated
30 days (but not 10 days) following lesions which included the lateral
septal nuclei and the precommissural fornix; lesions which included the
medial septal and diagonal band nuclei and the main septal projection to
the hippocampus did not alter hippocampal receptor concentrations at
either 10 or 30 days after the lesions (Bohus, Nyakas and de Kloet,
1978; Nyakas, de Kloet and Bohus, 1979). Following unilateral dorsal
3
hippocampectomy the concentration of [ Hjcorticosterone binding sites in
the contralateral hippocampus was increased by 74% and 41%, respec¬
tively, 10 and 20 days after lesioning (Nyakas, de Kloet, Veldhuis and
Bohus, 1981). Thus, some hippocampal afferents and efferents may
modulate steroid receptor concentrations.
Corticosterone "Membrane Effects" and Receptors
Some corticosteroid effects on the nervous system are not mediated
by the mobile cytoplasmic receptors that affect gene expression; these
effects may derive from the alteration of membrane properties by the
free steroids themselves or may be mediated by specific membrane-
associated receptors. Proposed mechanisms for such effects have
included the stabilization of lysosomal membranes, which could delay the
release of hydrolytic enzymes; alteration of ribosomal attachement to
the endoplasmic reticulum, which could modify protein synthesis; and
alteration of the binding of calcium to intracellular membranes, which
could influence synaptic function (reviewed in Baxter and Rousseau,
1979; Nelson, 1980).

33
Dexamethasone appeared to elevate tyrosine hydroxylase activity in
the superior cervical ganglion of adrenally intact rats by exerting an
excitatory pharmacological influence directly on preganglionic
cholinergic nerve terminals; very large doses of corticosterone were
completely ineffective, and the slowly-developing effect of
dexamethasone was abolished by a cholinergic receptor antagonist (Sze
and Hedrick, 1979). The effects of synthetic glucocorticoids on
cholinergic neurotransmission have been both excitatory and inhibitory.
The excitability of cat somatic motoneurons was increased (Riker, Baker
and Okamoto, 1975), and the contraction of guinea pig ileum in response
to nerve stimulation was decreased (Cheng and Araki, 1978) by the
steroids; in both cases the evidence suggested a direct steroid action
on cholinergic terminals.
Systemic or local injection of glucocorticoids has been observed to
affect the spontaneous activity of neurons in many brain loci (for
review, see Feldman, 1981). Injection of cortisol in intact,
freely-moving rats rapidly increased spontaneous activity of units in
the anterior hypothalamus and mesencephalic reticular formation, and
decreased unit activity in the ventromedial and basal hypothalamus
(Phillips and Dafny, 1971a,b). Spontaneous activity of basal
hypothalamic neurons in completely deafferented hypothalamic islands was
also rapidly decreased following systemic injection of either cortisol
(Feldman and Same, 1970) or dexamethasone in intact rats (Ondo and
Kitay, 1972). Similarly, iontophoretic application of dexamethasone
onto medial basal hypothalamic neurons in intact rats produced an
immediate depression of cell firing (Steiner, Ruf and Akert, 1969).
Mesencephalic neurons also responded to direct application of

34
dexamethasone with a decrease in firing rate (Steiner et al., 1969), in
contrast to the increase in firing rate after systemic injection of
cortisol reported by Phillips and Dafny (1971a,b). The injection of
dexamethasone into the vicinity of the recording electrode rapidly
produced a dramatic decrease in hippocampal multiple unit activity
(Michal, 1974), but none of 500 hippocampal neurons tested were
responsive to iontophoretic application of either cortisol or corti¬
costerone (Barak, Gutnick and Feldman, 1977). It is not known if some
of these reported electrophysiological effects of corticosteroids are
mediated by specific receptors, but their short latencies suggest that
they are direct membrane effects not mediated by changes in gene
expression.
The membrane effects of glucocorticoids probably also include the
physiologically important fast feedback (FFB) suppression of the release
of CRH by hypothalamic neurons. The addition of corticosterone to the
in vitro incubation medium blocked the release of CRH produced by the
electrical stimulation of sheep hypothalamic synaptosomes (Edwardson and
Bennett, 1974), and there is evidence that the FFB action of corti¬
costerone, which is unaffected by a number of pharmacologic agents, may
be mediated by a direct stabilizing interaction of the steroid with the
membrane of the CRH-secreting cell, which decreases the flux of calcium
into its terminals (Jones et al., 1977).
3
Glucocorticoids regulate the uptake of [ Hjtryptophan by isolated
brain synaptosomes incubated in vitro with the steroids; corticosterone
and dexamethasone at concentrations above 10~^M elevated the maximal
rate (\L 1 of tryptophan transport by a high affinity synaptosomal
max
uptake system from mouse brain (e.g., Sze, 1976). This effect contrasts

35
sharply with the reversal by glucocorticoids of the increase in the V
max
of high affinity GABA uptake into rat hippocampal synaptosomes observed
after adrenalectomy (Miller, Chaptal, McEwen and Peck, 1978). The
latter effect required hormone pretreatment in vivo and was not observed
when the synaptosomes were incubated in vitro with glucocorticoids,
suggesting that in this case the steroid action was probably mediated by
the "classical" mobile receptor pathway.
Synaptic plasma membranes prepared from osmotically-shocked rat
brain synaptosomes have been reported to contain specific binding sites
for glucocorticoids (Towle and Sze, 1978). Specific, saturable binding
of [ H]corticosterone by synaptic membranes was greatest in the
hypothalamus, and lower (but approximately equal) levels were found in
hippocampus and cerebral cortex. The affinity of corticosterone for the
binding sites (Kd ^ 10~7M) was similar in the three brain regions, and
both corticosterone and synthetic glucocorticoids had similar affinities
for the membrane sites. Soluble cytoplasmic receptors and synaptic
membrane binding sites in brain are characterized by somewhat different
properties of thermal stability and resistance to hydrolytic enzyme
attack, making unlikely the possibility of artifactual contamination of
the membranes by cytoplasmic receptors. Since the affinity of
corticosterone for the membrane binding sites (Towle and Sze, 1978)
agrees well with the concentration-response relation for the in vitro
stimulation of synaptosomal tryptophan uptake by corticosterone (e.g.,
Sze, 1976), it is possible that the membrane binding sites are involved
in the regulation of tryptophan uptake in the brain.

36
Summary
Glucocorticoids have profound metabolic, neuroendocrine, and
behavioral effects in the mammalian brain (e.g., Rees and Gray, 1982).
Although some of the less-well-understood effects may result from direct
interactions of the steroid with components of target cell membranes,
many of the effects are thought to be mediated by interactions of the
hormone molecules with steroid-specific cytoplasmic and nuclear
macromolecular receptors that concentrate as activated hormone-receptor
complexes in the target cell nuclei, where they initiate the changes in
gene expression that produce the ultimate physiological effects. The
objectives of brain corticosteroid receptor research are to improve our
extremely limited understanding of the basic mechanisms of receptor
capacitation, activation, nuclear concentration and recycling; to
examine whether the receptor systems for corticosteroid hormones in
brain (and pituitary) resemble closely those operative in other target
tissues; and to determine how the components of the receptor system are
altered in the clinically relevant conditions (such as experimentally-
induced diabetes, genetically-determined obesity and hypertension, and
normal age-related brain senescence) that are correlated with changes in
receptor function.
The experiments presented in this dissertation have been designed
to examine a number of the specific physicochemical properties of
soluble mouse brain glucocorticoid binding sites. The mouse has been
chosen for this research for several reasons. Although a few published
studies have indicated the existence of receptors in the mouse brain
(e.g., Finch and Latham, 1974; Nelson, Holinka, Latham, Allen and Finch,
1976; Angelucci et al., 1980), no basic characterization of the kinetic

37
and equilibrium binding parameters or the steroid specificity of these
receptors has been reported. Although a modest body of literature
(reviewed above) concerned with the properties of rat brain gluco¬
corticoid receptors already exists, recent improvements in receptor
methodology have led us to believe that many of the published rat brain
results are probably questionable, and thus that complete reexamination
of the rat brain receptor system must eventually be undertaken.
Therefore, we have chosen the mouse primarily for obvious economic
reasons, and because it is relatively easy to rapidly perfuse and remove
a large number of mouse brains. The decision to use the mouse instead
of the rat has had little impact on the choice or design of specific
experiments.
Since it is necessary to eliminate both endogenous gonadal and
adrenal steroids before killing the animals, females have been used
because they can be simultaneously ovariectomized and adrenalectomized
through the same incisions. We have used whole mouse brain cytosol
because most of the experiments required large amounts of receptor
material and since there is no evidence that there are brain regional
differences in the physicochemical properties of corticosteroid
receptors. Since the use of smaller brain regions would not have
enabled us to distinguish between cell types, it was felt that the
additional expense and effort required to work with a smaller brain
region such as dorsal hippocampus would not be rewarded adequately.
We have used the labeled glucocorticoids [ Hjcorticosterone,
3 3
[ H]dexamethasone and [ H]triamcinolone acetonide (cyclic acetal).
3
[ H] Dexamethasone was used to perform both equilibrium and kinetic
3
studies; [ Hjcorticosterone was employed to examine the possible

38
. O
contribution of transport proteins to the total pool of [ H]corti-
costerone binding sites, whereas the nearly-irreversible ligand
[ H]triamcinolone acetonide was used for the lengthy procedures
examining the size and shape of the receptors. In contrast to many of
the older receptor studies with rat brain reviewed above, our
experiments have used a buffer containing ingredients that prevent loss
of unoccupied binding sites at 0-4°C; used a rapid assay that can both
measure association kinetics conveniently and assay rapidly-
dissociating binding complexes; considered the possible consequences of
the failure to allow adequate time for "equilibrium" incubations at low
ligand concentrations; determined steroid specificity by applying
mathematically correct procedures to the analysis of competition data;
explored the contribution of CBG-like binding sites to the total pool of
corticosterone binding sites, and examined binding site sizes and shapes
to assess the homogeneity of the in vitro receptor population. Before
presenting experimental data we discuss (in chapters II and III) some
simple applications of the binding rate equation and propose some
improvements to the methods of graphical analysis of equilibrium
competition data currently in use.

CHAPTER II
METHODS FOR THE DETERMINATION OF ASSOCIATION AND
DISSOCIATION RATE CONSTANTS AND FOR THE ESTIMATION OF TIMES
REQUIRED FOR THE ATTAINMENT OF ARBITRARY DEGREES OF APPROACH
TO EQUILIBRIUM BY NON-COOPERATIVE, SINGLE SITE
LIGAND-RECEPTOR SYSTEMS
Introduction
The rate equation for noncooperative, single site ligand binding
systems may be written
dBL/dt = ka (SL-BL)(B0-BL)-kdBL, (2-1)
where B^ is the concentration of specifically-bound ligand, S^ is the
total ligand concentration, Bq is the total concentration of binding
sites, kg and k^ are the second-order and first-order association and
dissociation rate constants, and t is the time of incubation. The exact
solution to this equation gives the value of B^ as a function of time
for the given incubation conditions if the rate constants (or the
equilibrium dissociation constant, K^, and one of the rate constants)
and the concentration of ligand and binding sites are known (e.g., De
Lean and Rodbard, 1979; Vassent, 1974). Thus, if nonspecific binding
and loss due to the inactivation of binding sites may be neglected as an
approximation, the solution to the rate equation provides an estimate of
the time required for any arbitrary degree of approach to the
equilibrium value of specific binding. As an example of its utility,
39

40
the solution to the rate equation has been used to examine the effect of
inadequate incubation time (during which equilibrium was not attained
under conditions of low ligand concentration) on measured "equilibrium"
dissociation constants (Aranyi, 1979; Yeakley, Balasubramanian and
Harrison, 1980). The solution to the rate equation can also provide
insight into several superficially paradoxical phenomena, such as the
observation that the degree of approach to equilibrium within a given
time is not always a monotonically increasing function of ligand
concentration (Vassent, 1974). We present a concise derivation of a
computationally convenient form of the solution and discuss several of
its applications. Methods for the determination of association and
dissociation rate constants (not requiring the complete solution to the
rate equation) are also discussed.
Theory
Equation (2-1) may be rewritten in the classical Ricatti form as
d6L/dt - kaB2-ka(KdL+SL+Bfl)BL+kaSLB0, (2-2)
where k^ has been replaced by At equilibrium dB^/dt=0 and thus
(at equilibrium)
BL ' (KdL+SL+B0)BL+SLB0 = °* (2-3)
This may be rewritten as
(bl-p)(bl-q) = 0,
(2-4)

41
where
P - /B
(2-5)
and
Q = (KdL+W[(KdL+SL+B0)2-4 \V1/2)/2- (2-6)
The smaller root, P, gives the value of at equilibrium. Now equation
(2-2) may be rewritten as
dBL/(BL-P)(BL-Q) = kadt, (2-7)
which, on integrating, gives
kat + c = (1n[(BL-P)/(BL-Q)])/(P-Q), (2-8)
where c is the integration constant determined by the initial condi¬
tions. If (B^)q denotes the value of B^ at t = 0 then
c = (ln[[(BL)0-P]/[(BL)0-Q]])/(P-Q). (2-9)
Upon substituting (2-9) into (2-8) we get
t = (ln[[BL-P][(BL)0-Q]/[(BL)0-P][BL-Q]])/ka(P-Q), (2-10)
and thus

42
exp [kat(P-Q)] = [Bl-P][(Bl)0-Q]/[(Bl)0-P][Bl-Q].
(2-11)
Solving for BL, we eventually find that
Bl = [P(d/e) - Q exp (-ft)]/[(d/e) - exp (-ft)],
(2-12)
where d = Q - (B^)q, e = P - (B^)q, and f = kQ(Q-P). If the initial
binding is zero (a common application), then equation (2-12) simplifies
to
Bl = [l-exp(-ft)]SLBQ/[Q-P exp(-ft)],
(2-13)
since QP = S^Bq. (This form of the solution is computationally
convenient because it avoids the generation of large exponentials as t
becomes large.)
The relative error or fractional deviation from equilibrium is
defined as
e = absolute value of [(BL~P)/P], (2-14)
and is easily calculated. If equation (2-12) and (2-14) are solved for
t (e.g., Vassent, 1974), then an expression giving the time required for
an arbitrary degree of approach to equilibrium is obtained:
t (e) = [l/ka(Q-P)] In ([Q—P(1-E)]/ P[l+(Q-P)/e]).
(2-15)

43
We now examine some applications of the rate equation and its
solution. In the following discussions we shall assume that Bq remains
constant with time (unless a deliberate dilution or concentration is
performed). Many in vitro steroid receptor preparations do not,
however, possess this stability. For example, a frequent observation
has been the gradual inactivation or loss, with time, of unoccupied
(free) receptor binding sites (e.g., Luttge et al., 1982). If this is
the case, then the rate equation (2-1) must be supplemented with the
simultaneous inactivation equation
d(B0-BL)/dt = -kin (Bq-Bl) - dBL/dt,
(2-16)
where k^n is an empirical inactivation constant describing a process of
simple unimolecular decay of the normal binding site conformation.
(This assumption has, of course, no theoretical basis; it is merely a
statement of the observation that the relative early regions of slow
receptor inactivation curves may be approximately fit to simple
exponentials.) Equation (2-16) simplifies to
(2-17)
which may be solved simultaneously with the rate equation (2-1) by
standard computerized numerical integration methods (e.g., Yeakley et
al., 1980).

44
Applications and Discussion
If the chosen binding assay can be performed rapidly then the
association rate constant may be determined conveniently by measuring
as a function of t for a relatively short period of time (during which
dissociation may be neglected) following the mixing of ligand with the
receptor preparation. If t is small then dissociation may be neglected
and equation (2-1) becomes simply
dBL/dt = ka(SL-BL)(B0-BL), (2-18)
which, upon integration with the initial condition that B^=0 at t=0,
gives
kat = [1/(SL-B0)] In ([B0(BL-SL)]/[SL(BL-B0)]). (2-19)
It follows immediately that
kat (SL-B0) = In (Bq/Sl) + In E(SL-B,_)/(BQ-BL)]. (2-20)
It is apparent that at short times a plot of In [(S^-BL)/(Bq-B^)3 as a
function of time will be a line with slope (S^-Bq). The ordinate of
this plot is more easily remembered as In [(free 1igand)/(free
receptor)]. This method for the determination of k obviously requires
both knowledge of and an estimate of Bq derived from an equilibrium
experiment performed with the same receptor preparation.
It is also possible to determine the association constant ka by
measuring B^ following brief incubations of constant (short) duration

45
conducted at different ligand concentrations. These values of B^, when
divided by the incubation time, are taken as estimates of the initial
rate of increase of binding (dBL/dt), which is plotted on the ordinate
as a function of the total ligand S^. To analyze this experimental
strategy we note that since BL = 0 at t = 0, equation (2-1) reveals that
the initial rate of appearance of bound complex is given simply by
dBL/dt (at t=0) = BQkaSL. (2-21)
Thus, the plot of dB^/dt (initial) as a function of is a line
possessing slope Bq^. In fact, the observed curvature of such a plot
(a decrease in slope at high values of S^) has even been offered as
possible evidence that the glucocorticoid receptor binding process may
involve multiple steps and unobserved transient intermediate states
(Pratt, Kaine and Pratt, 1975). (The most probable explanation of this
anomaly is that the constant incubation time was too long to provide a
reliable estimate of the initial dB^dt at the high ligand
concentrations.) The two aforementioned experimental designs may be
combined, of course, by accumulating the early regions of temporal
binding curves generated at different ligand concentrations. The
individual binding curves will generate independent measurement of k
d
that should not be correlated with the ligand concentration S^.
Information (in the form of the derived values of k ) from the
cl
individual binding curves may also be merged by plotting (l/BgJdB^/dt
(initial) = k S. as the ordinate vs. S. as the abscissa for each
a L L
binding curve. The plot should pass through the origin, and the
resulting slope provides the merged estimate of k .
d

46
The dissociation rate constant kd is determined by simply measuring
the bound ligand as a function of time following some manipulation
that prevents any further association (or reassociation) of labeled
ligand with the receptors. Ordinarily this is accomplished by adsorbing
the free labeled steroid onto activated charcoal, followed by either
dilution of the preparation to further reduce the concentration of free
steroid to a negligible level or by the addition of a high concentration
of unlabeled steroid to dilute the specific activity of any remaining
labeled free steriod (and to dilute the labeled steroid that is released
into the free pool during the course of dissociation). Thus, since the
association of labeled ligand is blocked, equation (2-1) becomes
dBL/dt = - kdBL, (2-22)
where B^ now represents only labeled bound ligand. Upon integration we
obtain the familiar first order dissociation relations
ln[BL/(BL)0] = - kdt (2-23)
and finally
Bl = (Bl)q exp (-kdt), (2-24)
where (B^)q is the initial bound concentration at the beginning of the
dissociation period. The rate constant kd is simply the slope of the
plot of 1 n[B^/(Bj^)q] as a function of t. The dissociation rate is also
frequently reported as the half-life (t^) of the bound complex:

47
t1/2 = 0" 2)/kd. (2-25)
Depending on the experimental design, a measurement of the
dissociation rate constant may be performed under conditions of
decreasing, constant, or increasing receptor occupancy (B^/Bg). If no
unlabeled steroid is added, the occupancy obviously will decline.
(However, if unoccupied receptors are inactivated or degraded at a rate
comparable to the dissociation rate, then occupancy will not decline as
rapidly as B^ itself.) If the receptors are saturated at t=0, then
addition of a large amount of unlabeled ligand will maintain the high
level of binding. If the receptors are not initially near saturation,
then the addition of unlabeled steroid will lead to a condition of
rapidly increasing occupancy. If necessary, the concentration of
unlabeled ligand may be chosen to maintain a desired intermediate level
of occupancy. If the dissociation kinetics are biphasic or complex
under conditions of constant occupancy or saturation, then the
possibility of several classes of binding sites must be considered
(e.g., Weichman and Notides, 1979). If the kinetics are complex under
conditions of declining occupancy, then the possibility of cooperativity
must be considered; the experiment should then be repeated at high or
constant occupancy to see if the apparent cooperativity is really a
reflection of heterogeneity (e.g., DeMeyts, Roth, Neville, Gavin and
Lesniak, 1973).
If excess unlabeled steroid is not added to the preparation at the
beginning of the dissociation period, the possible reassociation of
newly-dissociated labeled ligand or the association of the small amount
of residual labeled steroid not removed initially may reduce the

48
measured apparent dissociation constant. The magnitude of this
reduction may be estimated approximately by using the solution to the
rate equation to monitor the relaxation of to the new, low-but-
nonzero value of P (equilibrium value of B^) in the following way.
First, assume for kd the (underestimated) value that has been measured
experimentally; call this value ^(apparent). A previously estimated
value of k or K.. must also be assumed; if a value of k is assumed,
a ql a
then KdL is taken to be kd(apparent)/ka. Measured values of SL, Bq, and
(B^)q are also available. Now equation (2-12) is used with these values
of the independent variables to calculate B^ for the same values of t at
which actual measurements of BL have been made. These calculated values
of B^(t) are then used to derive, from the slope of a plot of t vs. In
[calculated BL(t)/(BL)g], another underestimated dissociation rate
I I
constant, called k^. Next assume simply that the amount by which kd
underestimates kd(apparent) is equal to the amount by which kd(apparent)
underestimates the "true" value of kd that is sought. Thus
I
"true" kd - kd(apparent) kd(apparent) - kd, (2-26)
and finally
"true" kd 2 kd(apparent) - kd. (2-27)
This rough estimate of the correction is reasonable when is small.
The solution to the rate equation may also be used to predict the
error in a determination of derived from a "nonequilibrium" isotherm
generated by measurements performed before equilibrium has been attained
in the incubation vessels containing the lower concentrations of S^.

49
(Estimates of the rate constants and Bq are required, of course, in
order to perform this simulation.) A predicted value of BL is calcu¬
lated for each experimental value of SL (at the constant value of t used
for the incubation) using equation (2-13), and the resulting values are
used to construct the predicted (curved) Scatchard plot resulting from
the inadequate incubation time. A line is fitted to the points by the
same technique that is used to fit the experimental points (e.g., linear
regression), and a value of is derived from the resulting "slope"
(e.g., right inset to fig. 4-10). The entire procedure may be iterated
for different values of t in order to simulate the approach of the
apparent, measured KdL to its "true" equilibrium value as the incubation
time is prolonged. It is instructive to examine the dependence of the
relative error function upon SL; when combined with equation (2-13),
equation (2-14) becomes
e = (Q-P) exp(-ft)/[Q-P exp(-ft)], (2-28)
which is plotted as a function of in fig. 4-10 (left inset) for
several different incubation times using one specific set of the other
independent variables. It is apparent that e rises rapidly to a maximum
and then declines slightly as is decreased from a high concentration.
Thus, as is decreased below the transition zone, e becomes essen¬
tially constant at a value given by equation (2-29) below, which is
simply the limiting value of e as declines:
lim e (as is decreased) = exp(-ft) = exp C-kQt(].
(2-29)

50
Thus, if a time and receptor concentration Bq are chosen such that
equation (2-29) is reduced to an acceptable level, then very low values
of may be used to generate an isotherm. (More rigorously, one may
find by setting equal to 0 the partial derivative of equation (2-28)
with respect to S^, the exact nonzero value of that maximizes e; then
a time may be chosen that reduces this maximum relative error to an
acceptable level.)
Predicting the effect of the addition of a competing, cold ligand
(C) on the rate of approach to equilibrium of is a more complex
problem; this calculation requires the numerical integration of the two
simultaneous rate equations
dBL/dt = ka (B0-Bl-Bc)(Sl-Bl) - kdBL (2-30)
and
dBc/dt - kaC (Bq-Bl-Bc)(Sc-Bc) - kdcBc, (2-31)
where the subscript C refers to the competing ligand. Several
qualitative inferences can be drawn, however, from the fact that the
only effect of the competitor C is to decrease the free receptor
concentration in equation (2-30). Consider now the relative error e as
a function of Bq rather than of S^; since and Bq appear symmetrically
in equation (2-28), the left inset to fig. 4-10 also portrays the shape
of the plot of e considered as a function of Bq (with now held
fixed). If is sufficiently large, then the position of Bq will be to
the left of the maximum value of e on the plot; if is small enough,

51
however, the position of the same value of Bq will now be to the right
of the e maximum value. Thus, depending on the relations among S^, Bq
and K^, the effect of the reduction of free receptor concentration by
the competing ligand can be either to increase, decrease, or leave
essentially unchanged the value of e at a given time. Under the right
conditions a competitor may easily increase £ from near 0 to the maximum
value consistent with the given values of and t. (The rate constants
for ligand C and its concentration will, of course, affect £ by
determining how fast the competitor depletes the free receptor
concentration.) A very rough estimate of the effect of a high-affinity
competing ligand on the time required for B^ to approach equilibrium may
be obtained simply by assuming that the competitor is identical to the
labeled ligand. In this simple case becomes the sum of the labeled
and competing ligands, and equation (2-28) predicts £ for the total
bound ligand (B^ + Bq) for different times. Clearly this value of the
relative error also applies to B^, since for this special case
bL = SL (Bl+Bc)/(Sl+Sc). (2-32)
In order to facilitate estimation of the times required for the
approach to equilibrium under a variety of conditions, we present in
table 2-1 a short summary of solutions to the rate equation (2-1) for
several useful combinations of the variables Bq, S^, and (i.e.,
kj/ka) for the case of a single ligand and binding site. The initial
condition is simply (B^)q = 0, and the solution is presented as a table
of pairs of numbers representing the number of hours required for B^ to
attain 80% and 95%, respectively, of the equilibrium value. These

Table 2-1. Number of hours required for the concentration of specifically-bound ligand (B^) to reach 80%
and 95% (upper and lower number in each pair, respectively) of true equilibrium for a noncooperative, single
site binding system in which the second-order rate constant (k) equals lO^M'^min"^. For other values of
5 a
k multiply the tabulated values by 10 and divide the product by k . Bn is the total number of binding
a a U
sites, is the total ligand concentration and is the equilibrium constant.
-Log b 0
7
8
9
10
11
7
8
9
10
11
7
8
9
10
11
7
8
9
10
11
6
0.28
0.53
0.27
0.50
0.27
0.49
0.27
0.49
0.27
0.49
0.28
0.54
0.27
0.50
0.27
0.50
0.27
0.50
0.27
0.50
0.28
0.54
0.27
0.50
0.27
0.50
0.27
0.50
0.27
0.50
0.28
0.54
0.27
0.50
0.27
0.50
0.27
0.50
0.27
0.50
6.5
0.96
1.90
0.83
1.56
0.82
1.53
0.82
1.53
0.82
1.53
1.01
2.02
0.86
1.61
0.85
1.58
0.85
1.57
0.85
1.57
1.02
2.03
0.86
1.61
0.85
1.58
0.85
1.58
0.85
1.58
1.02
2.03
0.86
1.61
0.85
1.58
0.85
1.58
0.85
1.58
7
2.74
5.96
2.52
4.76
2.45
4.56
2.44
4.54
2.44
4.54
4.54
12.41
2.79
5.30
2.67
4.98
2.66
4.95
2.66
4.94
5.78
20.34
2.82
5.36
2.69
5.02
2.68
4.99
2.68
4.99
6.35
26.62
2.83
5.36
2.70
5.03
2.68
5.00
2.68
4.99
7.5
2.70
5.29
6.56
12.61
6.47
12.07
6.45
12.00
6.44
12.00
3.15
6.29
9.55
18.97
8.34
15.61
8.23
15.33
8.22
15.31
3.21
8.42
10.09
20.19
8.59
16.08
8.47
15.77
8.46
15.74
3.21
6.43
10.15
20.32
8.62
16.13
8.49
15.82
8.48
15.79
8
2.52
4.76
11.07
21.22
13.24
24.74
13.40
24.94
13.41
24.96
2.79
5.30
27.44
59.62
25.21
47.65
24.47
45.61
24.39
45.41
2.82
5.36
45.37
124.1
27.92
52.95
26.69
49.76
26.57
49.47
2.83
5.36
57.77
203.5
28.23
53.56
26.93
50.22
26.81
49.91
8.5
2.46
4.61
12.79
24.12
19.41
36.23
20.28
37.76
20.37
37.92
2.70
5.05
26.96
52.90
65.61
126.1
64.66
120.7
64.47
120.0
2.72
5.10
31.48
62.86
95.51
189.7
83.39
156.1
82.34
153.4
2.73
5.10
32.05
64.16
100.9
201.9
85.91
160.8
84.69
157.7
9
2.45
4.56
13.24
24.74
22.59
42.10
24.20
45.04
24.37
45.35
2.67
4.98
25.21
47.65
110.7
212.2
132.4
247.4
134.0
249.4
2.69
5.02
27.92
52.95
274.4
596.2
252.1
476.5
244.7
456.1
2.70
5.03
28.23
53.56
453.7
1241
279.2
529.5
266.9
497.6
9.5
2.44
4.55
13.36
24.90
23.79
44.31
25.76
47.96
25.98
48.35
2.66
4.95
24.64
46.09
127.9
241.2
194.1
362.3
202.8
377.6
2.68
5.00
26.97
50.49
296.6
529.0
656.1
1261
646.6
1207
2.69
5.00
27.23
50.98
314.8
628.6
955.1
1897
833.9
1561
10
2.44
4.54
13.40
24.94
24.20
45.04
26.30
48.96
26.53
49.39
2.66
4.95
24.47
45.61
132.4
247.4
225.9
221.0
242.0
450.4
2.68
4.99
26.69
49.76
252.1
476.5
1107
2122
1324
2474
2.68
5.00
26.93
50.22
279.2
529.5
2744
5962
2521
4765
10.5
2.44
4.54
13.41
24.96
24.33
45.28
26.48
49.28
26.71
45.72
2.66
4.94
24.41
45.46
133.6
249.0
237.9
443.1
257.6
479.6
2.68
4.99
26.60
49.54
246.4
460.9
1279
2412
1941
3623
2.68
4.99
26.84
49.99
269.7
505.0
2696
2590
6561
12612
11
2.44
4.54
13.41
24.96
24.37
45.35
26.53
49.39
26.77
49.83
2.66
4.94
24.39
45.41
134.0
249.4
242.0
450.4
263.0
490.0
2.68
4.99
26.57
49.47
245.0
456.1
1324
2474
2259
4210
2.68
4.99
26.81
49.91
267.0
498.0
2521
4765
11071
21217
11.5
2.44
4.54
13.41
24.96
24.38
45.38
26.55
49.42
26.79
49.86
2.66
4.94
24.39
45.40
134.1
249.6
243.3
452.8
264.8
492.8
2.68
4.99
26.56
49.44
244.1
454.6
1336
2490
2379
4431
2.68
4.99
26.80
49.89
266.0
494.4
2464
4609
12793
24116
12
2.44
4.54
13.41
24.96
24.38
4 5.39
26.56
49.43
26.79
49.87
2.66
4.94
24.39
45.39
134.1
249.6
243.7
453.5
265.3
493.9
2.68
4.99
26.56
49.44
243.9
4 54.1
1340
2494
2420
4504
2.68
4.99
26.80
49.88
265.7
494.7
2447
4561
13235
24743
Log KdL
« 8
- L°9 KdL
- 9
- L°9 KdL
- 10
- L°9 KdL “ 11
(J1
ro

Table 2-2. Fraction of specific binding sites occupied and the fraction of the total ligand
involved in that binding at equilibrium for a noncooperative, single site binding system.
Tabulated data are expressed as percentages with B^/Bg (x100) presented as the upper and
B^/S^ (xlOO) as the lower number in each pair. is the concentration of specifically-
bound ligand, Bg is the total number of binding sites, is the total ligand concentration
and is the equilibrium constant.
- Log bq
7
8
9
10
11
7
8
9
10
u
1
8
9
10
n
7
8
9
10
11
98.9
99.0
9977"
99.0
99.0
99.9
99.9
99.4
99.9
99.9
>99.9
>99.9
>99.9
>99.9
>99*4
>9775
>99.9
>99.9
>99.9
>99.4
9.9
1.0
0.1
<0.1
<0.1
10.0
1.0
0.1
<0.1
<0.1
10.0
1.0
0.1
<0.1
<0.1
10.0
1.0
0.1
<0.1
<0.1
95.7
96.8
96.9
96.9
96.9
99.5
99.7
99.7
99.7
99.7
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
>99.9
30.2
3.1
0. 3
<0.1
<0.1
31.5
3.2
0.3
<0.1
<0.1
31.6
3.2
0.3
<0.1
<0.1
31.6
3.2
0.3
<0.1
<0.1
73.0
90.1
90.8
90.9
90.9
90.5
98.9
99.0
99.0
99.0
96.9
99.9
99.9
99.9
99.9
99.0
99.9
>99.9
>99.9
>99.9
73.0
9.0
0.9
0.1
<0.1
90.5
9.9
1.0
0.1
<0.1
96.9
10.0
1.0
0.1
<0.1
99.9
10.0
1.0
0.1
<0.1
27.8
71.0
75.5
75.9
76.0
31.2
95.7
96.8
96.9
96.9
31.6
99.5
99.7
99.7
99.7
11.6
99.9
99.9
>99.9
>99.9
87.8
22.5
2.4
0.2
<0.1
98.6
30.2
3.1
0. 3
<0.1
99.8
31.5
3.2
0.3
0.1
99.9
31.6
3.2
0.3
0.1
9.0
38.2
48.8
49.9
50.0
9.9
73.0
90.1
90.8
90.9
10.0
90.5
98.9
99.0
99.0
10.0
96.9
99.9
99.9
99.9
90.1
38.2
4.9
0.5
<0.1
98.9
73.0
9.0
0.9
0.1
99.9
90.5
9.9
1.0
0.1
>99.9
96.9
10.0
1.0
0.1
2.9
14.6
22.7
23.9
24.0
3.1
27.8
71.0
75.5
75.9
3.2
31.2
95.7
96.8
96.9
1.2
31.6
99.5
99.7
99.7
90.7
46.1
7.2
0.8
0.1
99.9
87.8
22.5
2.4
0.2
99.9
98.6
30.2
3.1
0.3
>99.9
99.8
31.5
3.2
0.3
0.9
4.9
8.4
9.0
9.1
1.0
9.0
38.2
48.8
49.9
1.0
9.9
73.0
90.1
90.8
1.0
10.0
90.5
98.9
99.0
90.8
48.8
8.4
0.9
0.1
99.0
90.1
38.2
4.9
0.5
99.9
98.9
73.0
9.0
0.9
>99.»
99.9
90.5
9.9
1.0
0.3
1.6
2.8
3.0
1.1
0.3
2.9
14.6
22.7
23.9
0.3
3.1
27.8
71.0
75.5
0.1
3.2
31.2
95.7
96.1
90.9
49.6
8.9
1.0
0.1
99.0
90.7
46.1
7.2
0.8
99.9
99.0
87.8
22.5
2.4
>99.9
99.9
98.6
30.2
3.1
0.1
0.5
0.9
1.0
1.0
0.1
0.9
4.9
8.4
9.0
0.1
1.0
9.0
38.2
48.8
0.1
1.0
9.9
73.0
90.1
10
90.0
49.9
9.0
1.0
0.1
99.0
90.9
48.8
8.4
0.9
99.9
99.0
90.1
38.2
4.9
>99.9
99.9
98.9
73.0
9.0
<0.1
0.2
0.3
0.1
0.3
<0.1
0.3
i.«
2.8
3.0
<0.1
0.3
2.9
14.6
22.7
<0.1
0.3
3.1
27.8
71.0
10.5
90.9
50.0
9.1
1.0
0.1
99.0
90.9
49.6
8.9
1.0
99.9
99.0
90,7
46.1
7.2
>99.9
99.9
99.0
87.8
22.5
<0.1
<0.1
0.1
0.1
0.1
<0.1
0.1
0.5
0.9
1.0
<0.1
0.1
0.9
4.8
8.4
<0.1
0.1
1.0
9.0
38.2
11
90.9
50.0
9.1
1.0
0.1
99.0
90.9
49.9
».o
1.0
99.9
99.0
90. 8
48.8
8.4
>99.9
99.9
99.0
»0.1
38.2
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
0.2
0.3
0.3
<0.1
<0.1
0.3
1.6
2.8
<0.1
<0.1
0.3
2.9
14.6
11.5
99.»
50.0
9.1
1.0
0.1
99.0
90.9
â– 50.0
».i
1.0
99.9
99.0
90.9
49.6
8.9
>99.9
99.9
99.0
90.7
4 6.1
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
<0.1
0.1
0.1
<0.1
<0.1
0.1
0.5
0.9
<0.1
<0.1
0.1
0.9
4.9
12
90.9
50.0
9.1
1.0
0.1
99.0
90.9
50.0
9.1
1.0
99.9
99.0
90.9
49.9
9.0
>99.9
99.9
99.0
90.8
48.8
-Log *dL â– 
8
-L°g *dL
- 9
-L°g KdL -
10
-Log KdL
11
CJ1
CO

54
5 -1 -1
durations were calculated for k = 10 M min . For other values of
a
c
simply multiply the tabulated values by 10 and divide the resulting
product by kQ. Table 2-2 presents estimates of the fractional occupancy
of the binding sites (B^/Bq) and the fraction of the ligand bound at
equilibrium (P/S^) under the same hypothetical conditions as in
table 2-1. (These percentages apply to all values of k .)
d

CHAPTER III
LINEARIZATION OF THE TWO LIGAND-SINGLE BINDING SITE
SCATCHARD PLOT AND "ED " COMPETITION DISPLACEMENT
PLOT: APPLICATION TO iHE SIMPLIFIED GRAPHICAL
DETERMINATION OF EQUILIBRIUM CONSTANTS
Introduction
The affinity of a ligand for a particular class of binding sites is
measured frequently by constructing an isotherm describing the binding
of an available labeled ligand having specificity for the same set of
binding sites, first in the absence and then in the presence of a fixed
total concentration of the unlabeled competitive inhibitor whose
affinity constant is to be estimated (e.g., Ginsburg, MacLusky, Morris
and Thomas, 1977; Katzenellenbogen, Katzenellenbogen, Ferguson and
Krauthammer, 1978; Kono, 1975; for review of competition experimental
designs see Rodbard, 1973). The data resulting from such an experiment
are often analyzed by making the approximation that the concentration of
free competitive inhibitor is equal to the total concentration present
and therefore constant over the entire range of labeled ligand
concentration, since the effect of a constant concentration of free
competitive inhibitor on a Scatchard plot (Scatchard, 1949) describing
the binding of a labeled ligand to a single class of noncooperative
binding sites is solely to decrease the slope of the plot by a factor
which, in combination with the concentration of free competitive
inhibitor, yields immediately the equilibrium constant of the inhibitor
55

56
(Cantor and Schimmel, 1980). Thus, if the above approximation is valid,
then the affinity of the competitor results directly from the slopes of
the two straight lines and the total concentration of the inhibitor.
However, if the competitive inhibitor is not present in great excess
over the total concentration of binding sites, then the above
approximation will not be valid, the resulting Scatchard plot will be
curved (Feldman, 1972), and the error in the derived equilibrium
constant caused by making the approximation may be substantial. In the
present communication we suggest a simple procedure for eliminating this
error by linearizing the curved Scatchard plot resulting from this
experimental design.
The very popular competition displacement experimental design
(known as the "ED^q" method) also generates data that are somewhat
difficult to analyze in the laboratory without the aid of computerized
nonlinear regression techniques. Within this design one measures the
fraction of initially bound labeled ligand remaining bound at
equilibrium in the presence of increasing concentrations of the
unlabeled competitive inhibitor whose affinity is to be measured (e.g.,
Abrass & Scarpace, 1981; Lindenbaum & Chatterton, 1981; for review, see
Rodbard, 1973). The total concentration of inhibitor that displaces
half the initially bound labeled ligand ("ED^g") is determined, and one
then attempts to relate this inhibitor concentration to its actual
affinity for the binding sites. This design presents two major
problems: the curvature of the displacement plot makes the precise
determination of ED^g difficult, and the ED^g itself is often quite
different from, and difficult to relate to, the actual equilibrium
dissociation constant of the competing ligand. In many situations the

57
curvature of the competition displacement plot cannot be eliminated
simply by performing a "logit-log" transformation (e.g., De Lean, Munson
and Rodbard, 1978) of the data. Furthermore, the use of approximations
(e.g., the Cheng-Prusoff (1973) formula) to relate the estimated ED5Q to
the equilibrium dissociation constant of the competitor is often
inappropriate and can lead to substantial additional error.
We now suggest that if the initial receptor occupancy is not too
high this experimental design can also be analyzed without approximation
by the simple procedure (to be described) that we recommend for
linearization of the curved, two-ligand Scatchard plot obtained in the
presence of a fixed concentration of competitive inhibitor. With this
method the equilibrium dissociation constant is obtained directly,
obviating calculation of the ED^q value itself. Furthermore, a more
nearly exact approximation that can be used to relate ED^q estimated
from an approximately linear logit-log plot of the competition
displacement data to the actual affinity of the competitive inhibitor
for the binding sites is presented. This method is particularly useful
when the initial receptor occupancy is rather high.
Theory and Application
The nomenclature for the two ligand-one binding site problem will
be as follows: and are, respectively, the concentrations of
specifically bound labeled ligand L and competitive inhibitor C. The
total concentration of binding sites is Bq. The equilibrium
dissociation constants for the binding of the labeled ligand and
competitor are, respectively, and K^; and and are the total
concentrations of these ligands. The free (unbound) concentrations of

Fig. 3-1. Theoretical Scatchard plots for a single ligand and for two ligands in
competition for one class of noncooperative binding sites. Inset:
linearization of the curved Scatchard plot by plotting the total concentration
of occupied binding sites (B^+Bq) on the abscissa.
The parameters used to generate the plots describe the binding of estradiol (E^) and
estriol (Eg) to the nonactivated calf uterine estrogen receptor and were taken from
Weichman and Notides (1980). Upper straight line: Ey alone, equilibrium dissociation
-10 ^
constant = 1.7 x 10 M; lower curved plot: E^ in the presence of 1 nM estriol (E^,
equilibrium constant = 2.6 x 10~^M). The concentration of binding sites (Bq) is 2.3
nM. The curved Scatchard plot for the purely competitive two ligand situation is a
hyperbola whose properties have been described (Feldman, 1972). The actual points on the
curve are purely hypothetical and were placed on the plot to indicate how specific binding
values map into the linearized coordinate systems shown in the inset and in Fig. 3-2 and
discussed in the text. The slope of the transformed plot remains the same (-l/KdL) as
that of the original linear plot generated by the single labeled ligand (E^), as does the
intercept on the x-axis (Bq).

15-
en
«X>

60
the ligands are Fg and Fg. In order to discuss the "EDgg" experimental
design we let (Bg)g and (Fg)g represent the initial values of Bg and Fg
when Sg=0. ED^q is the value of Sg when Bg has been reduced by half
(i.e., when B = (Bg)g/2), and we let F^q and Fg^g represent the
corresponding values of Fg and Fg (i.e., when Sg = EDgg).
As the first illustrative example we have used the equilibrium
dissociation constants that describe the binding of estradiol (Eg) and
estriol (Eg) to the nonactivated calf uterine cytosol estrogen receptor
(Weichman and Notides, 1980) in order to generate the purely
hypothetical Scatchard plots (Fig. 3-1) of theoretical data that would
be observed for the binding of labeled Eg, first in the absence and then
in the presence of Sg = 1 nM "cold" Eg. (The experimental design under
discussion here was not employed by Weichman and Notides (1980); we have
merely used the affinity constants, which were measured and reported
appropriately by these authors.) The concentration of binding sites
Bq = 2.3 nM is also taken from Weichman and Notides (1980); the
equilibrium constants are K^g = 1.7 x 10~^M (for Eg) and
K^g = 2.6 x 10~^M (for Eg). The linear Scatchard plot (for the case
Sg = 0) is, of course, described by the standard equation (e.g.,
Rodbard, 1973; Scatchard, 1949):
Bl/FL ’ - /KdL f3-1)
and thus has slope (-1/K^g) and intercept Bq on the x-axis (Fig. 3-1).
The lower, curvilinear Scatchard plot (Fig. 3-1) for the purely
competitive two ligand situation is a hyperbola whose geometric

61
properties have been described by Feldman (1972) and whose equation is
(Feldman, 1972; Rodbard and Feldman, 1975)
BL/FL - KdC[-1-(BL+SC-Bo)/KdC+['1-[BL+SC-V/Kdc)2
+ 4VKdC^/2]/2KdL- <3-2>
This hyperbolic Scatchard plot has one asymptote with slope (-l/KdL)
parallel to the linear Scarchard plot and an x-intercept (Bq-S^.), and
another horizontal asymptote below the x-axis at BL/FL = (-Kdc/KdL).
The actual points on the curve are completely hypothetical and have been
calculated and placed on the plot at equally spaced intervals of
(0.275 nM) in order to indicate how specific binding values map into the
modified coordinate systems to be discussed.
We now calculate the error in the derived value of resulting
from the assumption that the concentration of free inhibitor F^ is
constant in this experiment and therefore that the expression (derived
from simple Michaelis-Menten kinetics for the case of pure competitive
inhibition) sometimes called the Edsall-Wyman equation (Cantor and
Schimmel, 1980) is valid when applied to some estimate of the "slope" of
this (actually curved) plot. The Edsall-Wyman equation can be
rearranged to the convenient "Scatchard" form given by
(cf. equation 3-1)
Bl/Fl - - (BL-B0)/KdL(l+Fc/Kdc).
(3-3)

62
Thus, it predicts simply that the slope of the Scatchard plot will be
reduced by a factor of 1/(1+Fc/Kdc) in the presence of a constant
concentration of free inhibitor F^. We now substitute the total
concentration for the (actually variable) free concentration Fj..
Thus, the estimated value of KdC derived from the use of this
approximation (which we call K^app) will be given by
Kdc(app) = [reduced slope/(original slope-reduced slope)]S^.
(3-4)
Thus, the percentage error (E) will be given by
E/100 = [KdC(app)/KdC]-l (3-5)
and hence, from above,
E/100 = reduced slope)/Kd^[l+Kd^(reduced slope)]-l.
(3-6)
For the "reduced slope" we substitute the derivative of the equation of
the curvilinear Scatchard plot, d(B^/FL)/dB^, obtained directly from
equation (3-2) above. Thus, if the error is estimated by using as the
"reduced slope" the slope of the tangent to the curve at the abscissa
B^ = Bq/2, then the error in the derived equilibrium constant is given
explicitly by
E/100 = (Kdc[Sc-Kdc]Y-X[Sc+Kdc])/(Kdc2Y+KdcX),
(3-7)

63
where X = S^-K^^-ÍBq/Z) and
Y - ([l-(2Sc-B0)/2Kdc]2+4Sc/Kdc)1/2.
Thus, the error is independent of and vanishes under the ideal
conditions approached when » Bq and In the hypothetical
example involving estradiol (E^) and estriol (E^) the error resulting
from the use of this approximate method is large: the derived
(calculated from the slope obtained from a linear regression on the
eight hypothetical points shown on the curvilinear Scatchard plot in
-9
Fig. 3-1) for E3 is 1.6 x 10 M, whereas the actual value used to
generate the curve is 2.6 x 10~^M, a 5-fold discrepancy. In fact, a
significant and variable fraction of the competitor E^ is obviously
bound to the receptors in this hypothetical experiment.
The error discussed above may be avoided by analyzing the data from
the same experimental design in a slightly different manner. At
equilibrium the simple mass action rate equations for the binding of the
two ligands may be written as
(Bo-BL-BC)FL " KdLBL and
(3-8)
0 L C' L
(3-9)
which suggest immediately the "linearized Scatchard" forms given by
bL/Fl * - [(BL+Bc)-B0]/KdL and
(3-10)

64
VFC " ^BL+BC^"B0^KdC (3-H)
Thus, if B^/F^ or Bq/Fq on the ordinate are plotted against (Bq + Bq) on
the abscissa, then a linear "Scatchard-1 ike plot with slope (-1/K^) or
(-1/Kdc) and x-intercept Bq results (insets to Figs. 3-1 and 3-2).
Furthermore, since Bq (as well as K^) is derived from an initial
Scatchard plot constructed in the absence of the competitor, K^q may be
measured simply by plotting [Bq-Bq-Bq, (free binding sites)] on the
abscissa against Bq/Fq on the ordinate, as suggested by equation (3-9).
The resulting plot (Fig. 3-2) must pass through the origin and possess
slope (1/K^q). This is the analysis we recommend for the determination
of KdC by this experimental method.
The implementation of this analysis is scarcely more difficult than
the method that we have criticized: the only additional requirement is
the calculation of Bq and Fq for each data point. We note that Bq and
KdL have been determined already from an initial Scatchard plot.
Equation (3-8) is now rearranged to give
Vbl'bc - KdiA/FL- <3-12>
Thus, the abscissa of the recommended plot is determined directly from
equation (3-12), as is the value of Bq = [Bq-B^-(^dLBj_/F^)]. Since Sq
is known, Fq ^ Sq-Bq. (Note that nonspecific binding of the "cold"
competitive ligand must still be neglected, unless it can be estimated
from other experiments, e.g. Katzenellenbogen et al., 1978). The
best-fitting straight line passing through the origin is then fit to the
points as shown (Fig. 3-2), and the reciprocal of its slope is then

Fig. 3-2. Linearization of the curved Scatchard plot shown in Fig. 3-1.
The same hypothetical data points presented in Fig. 3-1 are shown plotted in the
coordinate system recommended for the determination of K^. The ordinate (B^/F^) now
refers explicitly to the concentrations of bound and free competitor (E^), and the
concentration of free binding sites (BQ-BL-BC) is plotted on the abscissa. The plot must
pass through the origin, and the slope (l/KdC) is the reciprocal of the dissociation
constant of the competitor (E^). The inset is analogous exactly to the inset of Fig. 3-1
the points are plotted with the total concentration of bound sites (B^B^) on the x-axis.
In this "Scatchard format" the slope is (-1/K^) and the x-intercept is again Bq.

0.5
1.0
[B0- Bl-Bc] (nM)
1.5
cn
CX>

67
determined. For statistical reasons it may be advisable simply to apply
the least squares criterion (i.e., to use the method of simple linear
regression) and not force the line to pass through the origin. Since
the plot of B^/F^ vs. [free binding sites] is used to estimate only one
binding parameter (K^), data sets arising from experimental
preparations differing in total binding site concentration may be merged
prior to the final analysis.
We have extended the analysis presented above to cover a very
limited case of the two ligand-two binding site problem: the method has
been used to "linearize" data resulting from investigation of the
specific mouse brain glucocorticoid receptor in crude cytosol containing
significant amounts of CB6 (transcortin). We have measured the affinity
of "cold" dexamethasone (which has negligible affinity for CBG) for the
specific [ Hjcorticosterone, non-CBG, binding sites (putative receptors)
in CBG-containing brain cytosol in order to compare the resulting
equilibrium constant with that obtained by using [ H]dexamethasone
itself to construct a one-ligand Scatchard plot. The experiment is
performed by first constructing separate sirigle-1 igand binding isotherms
3 3
using [ H]dexamethasone and [ Hjcorticosterone; then an isotherm
3
describing the binding of [ Hjcorticosterone in the presence of a fixed
concentration of dexamethasone is constructed and analyzed. (The same
cytosol preparation is used throughout, of course.) This analysis is
simplified dramatically both by the absence of a significant interaction
of dexamethasone with CBG and by the observation that the one-ligand
[ Hjcorticosterone Scatchard plot is not biphasic, which suggests that
the affinity of corticosterone for CBG is very similar to its affinity
for the putative receptors.

68
In order to describe the analysis we extend slightly the
nomenclature used above; this nomenclature will apply only to the
specific two-ligand, two-site isotherm to be "linearized." Bg and Bg
are the total concentrations of specifically bound [ Hjcorticosterone
and "cold" dexamethasone, respectively. BgR and BgT are the
concentrations of [ Hjcorticosterone bound to the putative receptors and
to CBG (transcortin), respectively. (Thus, Bg = BgR + Bgy). B^^ is
the total concentration of all binding sites, composed of Bg putative
glucocorticoid receptors and Tg transcortin binding site
(BMAX = B0 + V- KdL describes (approximately) the common affinity of
3
[ Hjcorticosterone for both the receptor and CBG binding sites, and K^g
is the equilibrium constant for the binding of dexamethasone to the
glucocorticoid receptor sites. Fg and Fg are the concentrations of
3
unbound (free) [ Hjcorticosterone and "cold" dexamethasone,
respectively.
From the mass-action equations (cf. equations 3-8 and 3-9 above) we
have the following:
(Bg-BLR-Bg)Fc = ^gBg,
(3-13)
%BLR-Bc)FL = KdLBLR’
(3-14)
(VBLl)FL = KdLBLT
(3-15)
and, adding equations (3-14) and (3-15) we get
(BMAX-BL-BC>FL = KdlA-
(3-16)

69
Since dexamethasone does not bind to CBG, recall that the plot of Br/Fr
as ordinate vs. abscissa [(BQ-BLR-BC), free receptor sites] is a line
passing through the origin with slope (1/K^). This is the plot used to
find Kdc for dexamethasone by competition with [ H]corticosterone.
The calculation deriving from the competition data is
straightforward. Bq is determined from the one-ligand isotherm of
O
[ H]dexamethasone binding, and B^^^ and Kd^ are derived from the
one-ligand [ Hjcorticosterone plot; Tq is then estimated from the
relation Tq = B^-Bq. The abscissa, [free glucocorticoid receptor
sites], is now rewritten as
B0‘BLR“BC = ^MAX'W ' (T0'BI_t); (3-17)
i.e. [free receptor sites] = [total free sites]-[free CBG sites].
Substituting from equation (3-16) above we obtain for the abscissa
6- <3-18>
Solving equation (3-15) for B^ and substituting the resulting
expression into equation (3-18) yields finally the computational form
for the abscissa:
B0"BLR~BC = Kdd • VJ- <3-19>
Now only Bq must be found, since Fq and Bq/Fq follow immediately. The
calculated value of the abscissa, [free receptor sites], is used to find
Bq from the identity

70
Bg = Bq-Blr- [free receptor sites].
(3-20)
By substituting the expression for B^R obtained from equation (3-14)
into equation (3-20) above, the convenient computational form for Bg is
found to be
Bc = B0 - [free receptor sites] (1+F^/K^^).
(3-21)
The estimate of K^g then follows directly from the slope of the
recommended plot described above.
We now turn to an analysis of the "ED5g" experimental design.
Figure 3-3 depicts theoretical competition displacement curves generated
by the same binding parameters (taken from Weichman and Notides, 1980)
that were employed in the construction of figs 3-1 and 3-2 and used in
the above analysis of the design in which the inhibitor is present at a
single concentration (the "Edsal1-Wyman" design). Furthermore, it is
presumed that K- and Bg have previously been measured in the absence of
competitor by constructing the one-ligand isotherm. If the initial
receptor occupancy [(B^Jg/Bg] is not too high, it is obvious that
linearization of the displacement curves may be achieved by plotting the
data in the same Bg/Fg vs. [Bg-Bg-Bg, free binding sites] coordinate
system discussed above in connection with the Edsall-Wyman experimental
design, using the same data manipulations to determine the abscissa and
ordinate of the plot (shown as inset to fig. 3-3). If the initial
receptor occupancy is too high, then the range of the plot will be
compressed severely and this method will not be useful.

Fig. 3-3. Theoretical curves for the competitive displacement of ligand L by ligand C
from a single class of noninteracting binding sites.
Upper curve: fraction B^/(Bl)q of initial bound ligand L remaining bound at equilibrium in
the presence of different concentrations (S^) of competitive inhibitor C; lower curve:
the bound/free ratio for ligand L at the various concentrations of competing ligand C.
Inset: linearization of the displacement curves by plotting the same data in the B^/F^, vs
free binding sites] coordinate system. Again, the slope is (1/Kdc). The
binding parameters used to generate the plots are listed in the legend to fig. 3-1 and are
the same in all figures. The initial receptor occupancy depicted in the figure is 50%,
and the concentrations of competitor C are spaced equally on a logarithmic scale.

2-
- LOG S,
~i
9.5
-0.8
-0.6
t 1 r
0.4 0.6 0.8 I
0-Bl-Bc] (nM)
-1.0
-0.4
(â– )
(BL>0
-0.2

73
Other methods must be used to determine from the displacement
plot when the initial receptor occupancy is too high. The direct
estimation of an ED^g value from the curved displacement plot (fig. 3-3)
is statistically naive, but a "pseudo-Hill" or logit-log transformation
of the data (fig. 3-4) may be used to approximate a straight line for
the estimation of ED^g by simple linear regression. The subsequent
calculation of «dc from the ED5Q estimate presents further difficulties.
We shall consider sequentially the problems of estimating ED^g and then
using this estimate to calculate Kdg.
The "logistic" equations (see De Lean et al., 1978, for review;
these are only approximations, as we shall demonstrate) that are used to
transform the competition displacement data of fig. 3-3 into the
approximately linear logit-log plots shown in fig. 3-4 are the
foil owing:
Bl = (Bl)0/(1+Sc/ED50)1-0
(3-22)
and
(3-23)
(The above Hill coefficient or "slope-factor" of 1.0 in the logistic
equations is appropriate for non-interacting binding sites such as those
under consideration here.) These logistic equations may be immediately
transformed into the "pseudo-Hill" or logit-log expressions
logit [Bl/(Bl)q] = log (B,_/[(BL)g-BLJ) = log ED5Q - log Sg (3-24)

Fig. 3-4. Logit-log transformations of the competitive displacement data shown in
fig. 3-3.
Both curves share the same ordinate (logit [B^/(BL)q]), but the abscissae refer
respectively to the concentration of free competitor C (Fc, lower curve) and to the total
concentration of ligand C (S^, upper curve). The intersections with the dotted line
(x-intercepts) define the ED^q and F^q for the given conditions, but neither is a good
estimate of K^. The slopes of the ED^q and F^q plots determined by simple linear
regression are, respectively, -1.22 and -0.91. The nonlinearity of the ED^q logit-log
plot is quite apparent. The use of estimates of ED^q and FC5Q to determine KdC is
discussed in the text.

2.0-
.5-
1.0-
LOG
Bl
Ebl\)_bl] °-5"
0.0-
-0.5-
10.0
9.5
-LOG Fc0

76
and
logit [Bl/(Bl)0] = log (BL/[(BL)Q-BL]) = log FC5Q - log Fc,
(3-25)
which may be fit (approximately) to the binding data by simple linear
regression. If equations (3-22) and (3-24) were exact, then the ED5Q
plot (upper curve, fig. 3-4) would be linear; if equations (3-23) and
(3-25) were exact, then the FC5Q plot (lower curve, fig. 3-4) would be
linear. Equations (3-23) and (3-25) are (as we will show) always better
approximations than equations (3-22) and (3-24). In the example under
consideration equations (3-23) and (3-25) provide an excellent
near-linear transformation of the binding data, as one can see upon
examination of fig. 3-4; the nonlinearity of the ED^q plot, however, is
quite apparent in this example.
We shall now derive the exact (but not computationally useful)
expression for logit [B^/(B^)q] and then note the condition under which
it may be approximated by equations (3-24) and (3-25). If the
Edsall-Wyman equation (3-3, above) is combined with the obvious initial
condition
(Bl)0 - B0(FL)0/[KdL+(FL)0],
(3-26)
then we obtain, upon eliminating Bq from equations (3-3) and (3-26),
(3-27)

77
where the constant = [(FL >0 + KdL]/(FL>0 = 1 + KdL/(FL>0- Fronl
equation (3-27) we immediately obtain
BL/C(BL)0'BL] = ClFL/[KdL(1+FC/KdC)+FL(1“Cl)]* (3-28)
which, upon elimination of Cj from the denominator and division by
FLKdi> yields
BL/[(BL)0_BL] = (Cl/KdL)/[(1/FL)(1+FC/KdC)-(1/(FL)0)]-
(3-29)
Thus, the exact logit-log equation is given by
logit [Bl/(Bl)0] = log (Cj/K^)
- log [(1/FL)(1+Fc/Kdc)-(1/(FL)0)], (3-30)
which is not computationally useful (since the term for the logit-log
abscissa itself contains the unknown K^). If, however, we may assume
that F^ is approximately constant over the entire range of (i.e.,
that F^ ^ (F^)q), then equation (3-30) reduces to the simplified form
logit [BL/(BL)0] % log [C^F^/K^] - log Fc, (3-31)
which is the linear logit-log plot equivalent to equation (3-25) above.
A comparison of equations (3-25) and (3-31) shows that the assumption F^
* (Fj^)q leads to the expression

78
FC50 - ClKdC^FL^O/KdL ~ KdC^1+^FL VKdlJ’ (3-32)
thus indicating clearly that Fg^g (and, of course, ED^g) is quite
different from the desired parameter K^g, which must be determined by an
additional calculation. Although the above approximation that leads to
linearization of the logit-log Fg plot (i.e., Fg ^ (Fg)g) derived
from the initial occupancy condition (Bg)g << Sg, the approximate
linearity of the plot is fairly robust over a broad spectrum of
experimental conditions and depends only on the initial conditions
relating to the labeled ligand L. Specifically, the approximate
linearity of the logit-log Fg plot does not depend on the relative
affinity of the two ligands, (Kdc/KdL)* The ^°9it_l°9 Plot containing
log Sg as abscissa (the "ED^q" logit-log Sg plot), however, departs
significantly from linearity because the approximation Fg Sg is a poor
one at low values of Sg. If K^g >> K^g then the large values of Sg
required to achieve ligand displacement will also make this formula
approximately valid and thus lead to linearization of the simpler ED^g
plot. The calculation of Fg for the construction of the logit-log Fg
plot from the measured data has been described above (equation 3-12
combined with the relation Fg = Sg - Bg), and the initial binding (Bg)g
may either be measured directly or calculated from the values of K^g and
Bg (in combination with the known Sg) measured previously. In the
specific example under consideration simple linear regressions of the
theoretical logit-log data of fig. 3-4 yield the following results:
[ED5g (lin. regress.)/"true" EDgg] = 1.12 (13% error), and [Fg5Q (lin.
regress.)/"true" Fg^g] = 0.999 (0.1% error). (The "true" values of
EDgg and Fg^g are, respectively, 4.80 and 3.20 nM.)

79
Further analysis is, of course, required to calculate Kdc from the
estimates of either ED^q or Fq5q obtained from the logit-log plots
discussed above. If, in equation (3-32) above, Fq5Q is replaced by ED
50
and (Fl)0 by Sq, one obtains the Cheng-Prusoff (Cheng and Prusoff, 1973;
Munson and P.odbard, 1980) correction
KdC^ ED50/(1+SL/KdL)* (3-33)
This formula is derived from equations (3-2) and (3-3) above by using
the definition of ED5Q (i.e., that (Bl)q = 2B^ when Sq = ED5Q) and
applying the drastic approximation that both Fq ^ Sq and Fq % Sq. As
the illustrative example will demonstrate, this does not provide a good
estimate of when the affinity of the competing ligand is too high.
We now show that this Cheng-Prusoff correction can be improved
substantially by including in the calculation the value of (Bq)q, which
easily can be measured experimentally or calculated from the values of
KdL and Bq measured previously. Combining the above equations (3-3),
(3-23) and (3-26) yields, upon elimination of Bq, the expression
^FL^0FC50^KdL + (FlJo-^FC50+iy - FL/^Kdl_(1+FC/lW+FlJ *
(3-34)
which, when evaluated at the 50% displacement point, becomes
(FL)0/2[KdL+(FL)0] a, FL5o/tKdL^1+FC50/l<:dC^+FL50-''
(3-35)

80
(Expressions (3-34) and (3-35) above are not exact, since they are
derived from the logistic equation (3-23), which is itself only an
approximation.) Since F^q = S|_ " (Bg)g/2 and = SL " ^BL^0 we
finally obtain, after elimination of F^g and (Fg)g and some
rearrangement and simplification,
KdC - FC50 x 2KdL^SL"^BL^0^^BL^0 + 2SL
+ 2SLKdL-3SL(BL)0]. (3-36)
This is a much better approximation than the Cheng-Prusoff
equation (3-33), to which it reduces when (Bg)g is neglected and Fg5Q is
replaced by ED^g. Equation (3-36) remains approximately valid, and is
still superior to equation (3-33), when ED5q is substituted for Fg^:
KdCiED50x2KdL[SL-0^ + 2SLKdL-3SL(BL)g]. (3-37)
Equation (3-36) will, however, always be superior to equation (3-37);
similarly, the Cheng-Prusoff expression itself will always be more
nearly exact if a good estimate of Fg5g is substituted for the estimate
of EDgg. Table 3-1 lists, for the example that we have been
considering, the K^g estimates derived from the two different
approximations; each method has been used in combination with both the
estimated and the exact values of Fg^g and ED^g listed above. It will
be seen that the retention of (Bg)g in the approximation is required for

Table 31. Estimates of K^c (The assumed exact value is 2.632 x 10^M) derived from the
Cheng-Prusoff correction and from the approximations described by equations 3-36 and
3-37. The inputs to the equations include both the exact values of F^q and ED^q for
the example discussed in the text and the estimated values derived as described from the
logit-log plots of Fig. 3-4.
Input ED50
Input FC50
Exact
Estimated
Exact Estimated
Cheng-Prusoff
method (eqn. 3-33)
5.462 x
10"1 °M
6.107 x 10-10M
3.648 x 10"10M 3.644 x 10“10M
Method of eqns.
(3-36) & (3-37)
3.941 x
10"1°M
4.406 x 10‘10M
2.632 x 10'10M 2.629 x 10"10M

82
the accurate derivation of KrfC from the competition displacement data
under consideration here. The ease of implementation of equation (3-36)
suggests that it (or at least equation 3-37) should always be used
instead of the Cheng-Prusoff approximation.
Although the graphical linearization of competition data is
achieved most conveniently in the recommended coordinate systems
discussed above, it can be displayed in simple modifications of any of
the popular binding plots. For example, a modified "Lineweaver-Burke"
plot (Lineweaver and Burke, 1934) that is linear with slope (and
y-intercept 1.0) can be constructed by plotting (Bq-B^J/B^ on the
ordinate with 1/F^ on the abscissa. A modified "direct linear" plot
(Eisenthal and Cornish-Bowden, 1974) may even be used to estimate by
finding the median of the abscissae of the intersections where lines
plotted for each of the individual observations in the usual "direct
linear" parameter space (F^, B^) intersect the horizontal lines having
ordinates Bq-B^.
The problem of determining the best-fitting line for the
recommended Bc/Fc vs. [Bq-Bl-Bc, (free binding sites)] plot is similar
to the problem of regression for the original one-ligand Scatchard plot
and has, in this context, been adequately discussed (e.g. Cressie and
Keightley, 1979; Rodbard, 1973; Rodbard and Feldman, 1975). In
addition, by the very nature of the definition of logit [B^/(Bl)q], the
logit-log plots of competition displacement data are quite sensitive to
error in the measurements of B^ performed at the low concentrations of
the competing ligand. Although the assumptions underlying the use of
the method of least squares (e.g., uniformity of variance,
noncorrelation of error in the independent and dependent variables) are

83
clearly violated in both the Scatchard and logit-log transformations of
the data (e.g., Rodbard, 1973), the method of least square is still used
frequently as a convenient first approximation and is probably not too
seriously biased if "outliers" are few and if confidence intervals are
strengthened by repetition of the experiment. Thus, the method of
simple linear regression or of linear regression through a fixed point
(the origin) may be applied to the recommended B^/vs [free binding
sites] plot; the calculation for the latter (Pollard, 1977) is routine
and directly yields
KdC = 1/slope = KdL?(BL/FL)1/z(BL/FL)1(Bc/Fc)i. (3-38)
The approximate analysis of variance and confidence intervals are given
in standard tests (e.g., Pollard, 1977). It is also convenient to use
the simple and more "robust" median parameter estimates discussed by
Cressie and Keightley (1979). This procedure (Cressie and Keightley,
1979) may be used to determine and Bq from the initial Scatchard
plot; and then if the line is to be forced to pass through the origin,
the "free receptor" plot for the direct determination of may be
analyzed by calculating the median estimate
KdC = 1/slope = median of (BLKdLfrc//BCFrL^i * (3-39)
In any case, the statistical complexity of the experiment demands that
confidence in the parameter estimates obtained by any of the methods
discussed above must come from replication of the complete design.

84
Discussion
A simple procedure for linearizing the curved Scatchard plot of the
binding of a labeled ligand to a single class of noninteracting binding
sites in the presence of a fixed total concentration of competitive
inhibitor has been presented. Since the nonlinearity of the Scatchard
plot constructed in the presence of the inhibitor may not be apparent
upon visual inspection because of variance in the data, the method of
calculating the equilibrium constant of the competitive inhibitor
recommended above should be used unless it is known that the equilibrium
dissociation constant of the inhibitor (K^g) is much larger than the
total concentration of binding sites. The same procedure may also be
applied to the analysis of data derived from the "ED^g" competition
displacement experimental design (if the initial receptor occupancy is
not too high). In addition, a useful approximation (a generalization of
the Cheng-Prusoff formula) that may be used to relate the ED^g or Fg^g
estimates obtained from approximately linear logit-log plots of
competition displacement data to the actual affinity of the competitive
inhibitor for the binding sites has been presented.
Significant sources of error remain inherent in both experimental
designs and cannot be eliminated easily; these include nonspecific
binding of the competitive inhibitor and also the potential presence of
additional receptor sites having significant affinity for the
competitive inhibitor but negligible affinity for the labeled ligand.
Furthermore, the statistical characteristics of the simple graphical
methods suggested above currently remain untested and must eventually be
examined in detail by the Monte-Carlo simulation procedure (e.g. Thakur,

85
Jaffe and Rodbard, 1980); for example, the competition "free receptor"
plot is probably less sensitive to error in BQ and K^. when it is
"relaxed" (i.e., not forced to pass through the origin). Whenever
practical, a computer program (e.g., Munson and Rodbard, 1980) should be
used to fit binding isotherms by a weighted, nonlinear regression
technique performed with a relatively error-free independent variable.
The plot of B^/F^ vs [free binding sites] or the competitive
displacement logit-log plot may still be used to display the actual data
points and the fit of the resulting computer-generated parameters.

CHAPTER IV
EQUILIBRIUM BINDING CHARACTERISTICS AND HYDRODYNAMIC PARAMETERS
OF MOUSE BRAIN GLUCOCORTICOID BINDING SITES
Introduction
Glucocorticoids have profound metabolic, neuroendocrine, and
behavioral effects in the mammalian brain (for reviews, see: Bohus et
al., 1982; Rees and Gray, 1982). Although some of the less-
well -understood effects may result from direct interactions of the
steroid with components of target cell membranes, many of the effects
are thought to be mediated by interactions of the hormone molecules with
steroid-specific cytoplasmic and nuclear macromolecular receptors that
concentrate as activated hormone-receptor complexes in the target cell
nuclei, where they initiate changes in gene expression that produce the
ultimate physiological effects.
The experiments reported here examine a number of physiochemical
characteristics of soluble mouse brain glucocorticoid binding sites, in
order to determine whether the glucocorticoid receptor system in mouse
brain resembles closely that operative in other target tissues and-
species. Although a few published studies have reported the existence
of glucocorticoid receptors in the mouse brain (e.g., Finch and Latham,
1974; Nelson et al., 1976; Angelucci et al., 1980), no basic
characterization of the kinetic and equilibrium binding parameters or
the steroid specificity of these receptors has yet been reported.
86

87
Although a body of literature concerned with the properties of rat brain
glucocorticoid receptors already exists (for review, see: Bohus et al.,
1982), recent improvements in receptor methodology have made it possible
to study the brain glucocorticoid receptor system under conditions that
prevent receptor activation (nucleophilic transformation) and maximize
in vitro receptor stability, permitting the relatively lengthy
incubations and procedures required to generate equilibrium isotherms
and to investigate the size and shape of the receptors.
We have used the labeled glucocorticoids [ Hjcorticosterone,
3 3
[ H]dexamethasone and [ Hjtriamcinolone acetonide (cyclic acetal).
3 3
[ H]Dexamethasone and [ H]corticosterone were used to measure
equilibrium and kinetic binding parameters, whereas the
nearly-irreversible ligand [ Hjtriamcinolone acetonide ([ H]TA) was used
for the lengthy sedimentation and chromatography procedures required to
examine receptor size and shape. The experiments reported here have
explored buffer components and employed a buffer that prevents the loss
of unoccupied binding sites at 2°C; used a rapid and convenient binding
assay; considered the possible consequences of failure to allow adequate
incubation time when ligand concentrations are low; compared equilibrium
binding parameters derived from the same pool of experimental data by
several different methods of analysis; determined ligand specificity by
applying mathematically correct procedures to the analysis of steroid
competition data; observed that CBG-like molecules contribute
signficantly to the total pool of corticosterone binding sites, and
examined binding site sizes and shapes to assess the stability and
homogeneity of the in vitro receptor population.

88
Materials and Methods
Chemicals, Steroids and Isotopes
The [1,2,6,7- Hjcorticosterone (SA = 80 Ci/mmole),
3 3
[6,7- Hjdexamethasone (SA = 36 Ci/mmole) and [6,7- H]triamcinolone
acetonide (SA = 37 Ci/mmole) were purchased from New England Nuclear
(Boston, MA) and checked for purity by chromatography on 60 cm LH-20
columns (Sippell, Lehmann and Hollmann, 1975) or by thin layer
chromatography (TLC) on Silica Gel G (plates were developed in
cyclohexane : methyl ethyl ketone, 1:1, or in dichloromethane :
methanol, 24:1). All nonradioactive steroids were purchased from
Steraloids, Inc. (Wilton, NH). Additional radiochemicals
([^Cjantipyrene, [2-^H]deoxy-D-glucose, [^C]formaldehyde,
[carboxyl-^Cjinulin and [^Hjwater) and a [^Ijcortisol Solid Phase
Radioimmunoassay kit were purchased from New England Nuclear.
Chromatography and filtration supplies were purchased from Pharmacia
Fine Chemicals (Piscataway, NJ), Bio-Rad Laboratories (Richmond, CA),
Whatman, Inc. (Clifton, NJ), Brinkmann Instruments, Inc. (Westbury, NY),
and the Amicon Corp. (Danvers, MA). Rabbit antiserum to corticosterone
was a gift from R.H. Underwood and G.H. Williams (Peter Bent Brigham
Hospital, Boston, MA). Other chemicals and solvents were of the highest
purity available commercially.
Animals
All studies used adult female CD-I mice (outbred, 20-25g Charles
River Laboratories, Wilmington, MA) that were subjected to combined
ovariectomy and adrenalectomy 3-5 days prior to the experiment in order

89
to remove known sources of endogenous steriods. Ovariectomy and
adrenalectomy were performed bilaterally via a lateral, subcostal
approach under Nembutal anesthesia, and mice were given 0.9% NaCl in
place of drinking water. On the day of the experiment mice were
anesthetized with ether (in some cases a .5-1 ml blood sample was then
withdrawn directly from the heart) and slowly perfused (over a period of
5 min) through the heart with cold HEPES-buffered saline (3 ml,
isotonic, pH 7.6) to reduce blood-borne CBG contamination of the brain
tissue. The efficacy of this procedure was assessed by a [^Cjinulin
washout study (see Chapter V).
The effectiveness of the surgery was verified by measurement of
corticosterone levels in plasma samples obtained from some of the
adrenalectomized mice at the time of killing. This was accomplished by
radioimmunoassay (RIA) both with rabbit antiserum to corticosterone (by
a modification of the method of Underwood and Williams, 1972) and with
125
the New England Nuclear [ I]Cortisol solid phase RIA kit using corti¬
costerone to construct the standard curve. Plasma samples (10^,1) were
extracted with 1 ml dichloromethane and then dried down prior to RIA.
Buffers
For most of the experiments cytosol was prepared in buffer A: 20 mM
HEPES, 1 mM EDTA, 2 mM DTT, 10 mM Na2Mo04, 10% (w:v) glycerol, pH 7.6.
The effects of pH and of the dithiothreitol (DTT) and molybdate
(Na2Mo04) concentrations on binding site stability were explored in
several initial experiments, and gel filtration and sedimentation were
performed at elevated ionic strength (with the addition of KC1). In the
descriptions of these experiments buffer compositions are reported as

90
modifications of the basic buffer A formulation (e.g., buffer A - DTT,
buffer A + .15M KC1, etc.).
Cytosol Preparation and Aging
Brains were removed from the perfused animals and homogenized (20
strokes at 1000 rev/min) in 1-6 volumes of cold buffer A in a glass
homogenizer with a Teflon pestle milled to a clearance between the
pestle and homogenization tube of 0.125 mm on the radius (to minimize
rupture of the brain cell nuclei, as suggested by McEwen and Zigmond,
1972). The crude homogenate was centrifuged at 2°C for 10 min at 15,000
rpm (27,000 x g) in a 15 ml Corex centrifuge tube. The supernatant was
transferred to a 10 ml "Oak Ridge" polycarbonate tube, and the pellet
was washed by resuspension in half the initial volume of buffer A (used
for the homogenization) and recentrifugation at 2 C for 10 min x 27,000
g. The resulting supernatant wash was added to the original supernatant
in the "Oak Ridge" tube, which was then centrifuged at 2 C for 1 h at
106,000 x g (average) to produce the cytosol used in the incubations.
Approximately 2 h elapsed between the time of killing and termination of
the high-speed centrifugation. Cytosol protein concentrations for the
equilibrium experiments ranged from approximately 2 mg/ml (with
homogenization in 6 volumes buffer A, initial pellet then washed with 3
volumes buffer A) to 12 mg/ml (homogenization in 1 volume buffer A,
pellet washed with 0.5 volume additional buffer A). The cytosol protein
content was determined by a modification of the Lowry method (Bailey,
1967) using bovine serum albumin as the standard.
In several experiments cytosol samples were incubated without
steroid for variable lengths of time before labeling with the

91
3
[ H]steroid ligand (i.e., the cytosol was deliberately "aged" beyond the
approximately 2 h required for cytosol preparation). In such
experiments the duration of aging was measured from the time when
cytosol preparation was completed (t = 0).
In order to examine the subcellular distribution of glucocorticoid
binding sites in mouse brain the standard subcellular fractionation
scheme (Cotman, 1974) was employed to generated crude nuclear (P-|),
crude mitochondrial (P^), and microsomal (P3) fractions in addition to
the cytosol; the fractionation scheme was modified, in that buffer A
(which is hypertonic because it contains 10% glycerol) was used instead
of isotonic .32 M sucrose. The concentrations of high-affinity
glucocorticoid binding sites measured in the subcellular fractions
(other than cytosol) generated in this way were negligible, and thus
these hypertonically-produced particulate fractions were not further
characterized.
Binding Assays
O
The principal assay used to measure bound [ Hjsteroid was the DEAE
(Whatman DE-81) filter assay, modified from similar assays developed to
measure glucocorticoid and mineralocorticoid binding to cytosolic
proteins in liver and kidney (e.g., Warnock and Edelman, 1978; Santi,
Sibley, Perriard, Tomkins and Baxter, 1973). The 25 mm filters were
equilibrated at 0-4°C in buffer A and then washed 2 times with 2 ml
buffer A in a Millipore suction manifold. For each of the triplicate
assays that commonly were performed a 50 ul aliquot of the sample was
pipeted directly onto the moist filter and allowed to penetrate it for
at least 1 min. Filters were then washed with 5 x 1 ml buffer A,

92
suctioned to near dryness, and then transferred to scintillation vials.
Filtration was performed at 0-4°C in a cold room. Radioactivity was
determined by liquid scintillation counting at 38% efficiency following
the addition of 1 ml H^O and 10 ml Triton-toluene scintillation cocktail
(toluene-Triton X-100, 2:1; 2, 5-diphenyloxazole, 4.375 g/1; dimethyl
POPOP, 43.75 mg/1) and disruption of the filters by vortexing of the
vials. Alternatively, the filters were dried overnight in a warm oven
and then counted at higher efficiency in a toluene based scintillation
cocktail not containing Triton X-100. The efficiency of the DEAE filter
assay was determined (as described below) by two different methods and
found to be 76%.
In order to calculate the efficiency of the DEAE filter assay some
of the binding data obtained with it were compared with those obtained
from the same samples with a Sephadex G-25 mini column gel filtration
assay and with a dextran-charcoal adsorption assay. In the former
procedure 50 yl aliquots of the sample were loaded onto Pasteur pi pet
mini columns filled with 1.5 ml Sephadex G-25 equilibrated in buffer A;
following collection of a 0.51 ml fraction that was discarded, a 0.8 ml
void volume containing bound radioactivity was collected and assayed by
liquid scintillation in a Triton-toluene cocktail. The dextran-charcoal
adsorption assay was performed by adding the 50 yl sample aliquot to a
1 ml suspension of dextran-coated charcoal (0.5% Norit A activated
charcoal, Fisher; 0.05% Dextran T-70, Pharmacia); following incubation
at 0-4°C for 5 min with occasional vortexing the charcoal was pelleted
by centrifugation at 10,000 x g for 5 min. The supernatant was then
taken for the determination of bound radioactivity by liquid
scintillation counting.

93
Gel Chromatography and Gradient Sedimentation
The in vitro stability and molecular size of the receptors were
examined by Sephacryl S-300 chromatography and glycerol gradient
sedimentation. Concentrated cytosol prepared in buffer A + 150 mM KC1
was incubated at 2°C for 12-16 h with 10 nM [3H]TA or 10 nM [3H]TA and
200-fold excess of unlabeled TA. Following incubation, free [ H]TA was
removed by gel filtration in the same buffer on a large (1.5 x 98 cm)
Sephadex G-25 (fine) column. Samples from the void volume of the G-25
column (2 ml, approximately 5 mg/ml) were then chromatographed on a
column of Sephacryl S-300 (superfine, 1.5 x 98 cm) at 12 ml/h in the
same buffer (A + .15 M KC1). Fractions (2 ml) were collected, and 1 ml
aliquots of these were assayed for radioactivity by liquid
scintillation. (The remaining 1 ml from the relevant fractions was
saved for gradient sedimentation.) Distribution coefficients (K^) were
calculated from elution volumes (Vg), the void volume (VQ) indicated by
3
blue dextran, and the total liquid volume (V^) marked by [ H]water,
[^C]antipyrene and [2-3H]deoxy(D)glucose: = (Vg - VQ)/(- VQ).
The column was calibrated (figure 4-29) with 7 standard proteins
(chromatographed in separate runs as two different mixtures and detected
by absorbance at 280 nm), and the Stokes radius of the receptor complex
(R$) was calculated from regressions of Rg vs. several different
functions of the calibration values as shown in figure 4-30.
Standard curves were generated by the linear methods of Porath (1963)
and Ackers (1967), and by the nonlinear regression of Laurent and
Killander (1964). The methods of regression were in close agreement.
After locating the peak of the gel chromatographic profile, the
remaining 1 ml aliquots from each of the 5 fractions bracketing the

94
S-300 peak were pooled and concentrated 10-fold by ultrafiltration
(Amicon Minicon B-15 or Model 12 Ultrafiltration cell with PM 10
membrane) to a volume of 500 yl. Aliquots (250 yl) of the concentrated,
pooled S-300 fractions were then centrifuged at 2°C for 20 h at
234,000 g (average) through 5 ml gradients of 12.5 - 25% (w/v) glycerol
or 15 - 50% (w/v) glycerol prepared in the same buffer (A + .15 M KC1).
The cellulose nitrate tubes were punctured, and 175 yl fractions were
collected and assayed for radioactivity. The value of S2q w for a peak
was calculated from the linear regression of S^q w vs. sedimentation
distance (Martin and Ames, 1961) for the standard proteins, which were
run on parallel gradients as 250 yl samples in the same buffer (A +
.15 M KC1). The standard proteins ovalbumin (3.6 S), bovine serum
albumin (BSA, 4.3 S) and IgG (y-globulin, 7.4 S) were [^CH^J-methylated
(for detection) to low specific activity by the method of Rice and Means
(1971).
Assuming that peaks observed on the glycerol gradients corresponded
to the same molecular species resolved by S-300 chromatography, the
apparent sizes and shapes of the binding sites were determined by
standard methods (Siegel and Monty, 1966; Sherman, 1975). The Stokes
radius (R$) and sedimentation coefficient (S^q w) of the protein are
related to its apparent molecular weight by the relation
M 6ttNti20 x Rs x s20 ,W/ (1
vp20,w^’
(4-1)
3
where the assumed value of the partial specific volume (v = 0.732 cm /g)
was estimated as described previously by Sherman (1975). The viscosity
of H20 at 20°C (h2q) = 0.01002 poise (g. cm”^.sec"^), and the density of

95
H^O at 20°C (p2q w) = 0.9982 g/cm3; and Avogadro's number (N) = 6.023 x
23
10 /mole. The frictional ratio was determined from the relation
f/f0 = Rs[4*N/3M(v + ^20,w)]1/3’ (4-2)
where the partial specific volume of F^O at 20°C (^g w) = 1.00 cm /g
and the hydration state of the protein ( (i.e., no hydration) or6= 0.2 g/g, an estimate used to permit
comparison of our results with those reported by Niu, Neal, Pierce and
Sherman (1981). The axial ratios (b/a, prolate ellipsoid) were
calculated from the Perrin equation
f/f0 = O - p2)Vp2/3ln([l + (1 - p2)*]/p), (4-3)
where p = b/a = ratio of minor to major axes of the prolate ellipsoid;
some solutions to Perrin's equation have been tabulated by
Schachman (1959).
DEAE and Dye-Ligand Mini column Chromatography
3
Cytosol samples labeled with [ H]TA were chromatographed on Bio-Rad
DEAE Bio-Gel A minicolumns (column characteristics: total volume = 5 ml;
flow rate = 6 ml/h; fraction volume = 1 ml; maintained at 4°C). The
column was washed extensively and equilibrated with buffer A.
Concentrated cytosol prepared in buffer A was incubated at 2°C for 12-16
h with 10 nM [3H]TA or 10 nM [3H]TA and 200-fold excess unlabeled TA.
3
Following incubation, free [ H]TA was removed by gel filtration in
buffer A on a large (1.5 x 98 cm) Sephadex G-25 (fine) column. Samples

96
from the void volume of this column (1 ml, approximately 5 mg/ml) were
run into the DEAE minicolumn and washed in with 200 yl buffer A.
Binding was allowed to proceed (30 min), and the column was then washed
with 25 ml buffer A. Bound species were eluted with a 50 ml linear KC1
gradient (0 - 250 mM KC1 in buffer A); during column wash and elution
fractions were collected and assayed for radioactivity.
3
The potential binding of [ H]TA-receptor complexes to immobilized
triazine dyes was assessed with an Ami con Dyematrex screening kit
consisting of five different dye-agarose minimcolumns (and an agarose
control column). The columns (2 ml volume) were washed extensively and
equilibrated with buffer A. Following the removal of unbound [ H]TA,
cytosol samples (.5 ml, protein concentration 5mg/ml) equilibrated
previously with 10 nM [ H]TA were applied to the columns and washed in
with .1 ml buffer A. Binding was allowed to proceed (30 min), and the
columns were then eluted (stepwise) with the following series of
C
reagents (10 ml each, in buffer A): buffer A alone, 5 x 10 M
dexamethasone, 5 x 10 M progesterone, 10 mM ATP, 10 mM NADP, 130 mM
KC1 , 380 mM KC1, 2M urea + .25M NaSCN, 8M urea + .5M NaOH (no buffer).
The nine 10 ml fractions were collected and assayed for radioactivity.
Experimental Designs and Data Analyses
Equilibrium isotherms were generated by incubating a series of
pairs of identical cytosol samples (for a time sufficient to allow a
close approach to equilibrium in all tubes) at 2°C with increasing
3
concentrations of [ H] glucocorticoid and, for one of each sample pair,
a 200-fold excess of the unlabeled steroid. The problem of choosing an
incubation time that is adequate to allow close approach to equilibrium

97
but is not excessive has been discussed in some detail in chapter II and
will be addressed again below in Results. Bound [ H]steroid
concentrations were then assayed in triplicate for both tubes of each
pair in order to determine total binding (By) and nonspecific binding
(B^, binding in the presence of the 200-fold excess unlabeled steroid).
O
Specifically bound steroid (Bsp) was determined for each [ H]ligand
concentration by subtracting B..c from BT. The values of BT and B were
corrected for the measured efficiency of the DEAE filter assay (76%, see
Results below) before the data were further analyzed. Since for reasons
of signal strength it was not desirable to restrict the concentration of
binding sites such that bound ligand did not exceed a small fraction of
the total added ligand (Sy), further analysis of the data by
conventional methods required the calculation of the free [ H]ligand
concentration (F), which was found by subtracting By from the total
3
[ H]ligand (Sy), which was also measured for each pair of tubes.
Equilibrium isotherms were generated with the synthetic agonists
3 3
[ H]dexamethasone and [ H]TA in order to measure the concentration of
putative glucocorticoid receptors and their affinity (or affinities) for
these ligands. Isotherms were constructed with [ H]corticosterone
(and excess unlabeled corticosterone) to examine at once the complete
ensemble of binding sites for the natural glucocorticoid, a subset of
which resembled CBG and failed to bind DEX and TA. The binding of
[ Hjcorticosterone itself to the restricted set of putative
glucocorticoid receptors was examined by constructing isotherms in which
the contribution of dexamethasone-resistant (CBG-like) binding sites was
removed from the determination of specific binding (B ) by using 200X
s p
unlabeled DEX to saturate only the putative glucocorticoid receptors in

98
the "nonspecific" control tubes, allowing any corticosterone-specific or
otherwise CBG-like binders to remain labeled with [ H]corticosterone.
In several experiments (e.g., the study of the loss of unocupied binding
sites as a function of cytosol aging and temperature) the concentration
of binding sites was measured not by extrapolation from isotherms but
rather by single-point assays performed following incubation with
3
concentrations of [ H]1igand known to be nearly saturating; these assays
were also performed in triplicate with pairs of tubes containing
[BH]ligand and [BH]ligand + 200 X unlabeled steroid.
Equilibrium isotherms were analyzed by several different methods.
First, the values of B$p and F were used to construct conventional
Scatchard plots to which, when the points appeared to fall approximately
on a straight line (and thus to define a single class of noninteracting
binding sites), lines were fit by simple 2-parameter linear regression
according to the equation
Bsp/F = -{Bsp - B0>/Kd
sp
(4-4)
where is the equilibrium dissocation constant and Bq is the molar
concentration of binding sites; the slope and x-intercept of this plot
thus provide estimates of the affinity and binding site concentration
when a single ligand binds to a single class of noninteracting binding
sites.
It would be desirable to combine a number of separate isotherm data
sets constructed with cytosol pools having different protein
concentrations in a "merged Scatchard" analysis. In such an analysis
each value of B (expressed originally in molar units) would be
sp

99
normalized by the appropriate protein concentration and thus converted
to the units fmole/mg protein; the free ligand concentration (F) would
remain in molar units (e.g., nM). Following normalization of the Bsp
values the Scatchard plot would be constructed by plotting all points in
the conventional fashion, with the ordinate (B /F) now possessing the
units (fmole/mg protein)/nM and the abscissa (B ) having the units
fmole/mg protein. The regression line would then be fit by simple
2-parameter linear regression. This "merged Scatchard" plot could be
used to cumulatively analyze data from an experiment that has been
repeated many times; the underlying assumption is, of course, that the
functional receptor concentration and ligand affinity do not depend upon
the cytosol concentration.
Because the estimates of functional receptor concentration (Bq)
derived from individual Scatchard plots for different pools of cytosol
were highly variable, the method described above was not used. Instead,
a simple modification of the "merged Scatchard" plot that obviated the
above assumption was used to obtain a single, merged estimate of for
comparison with estimates produced by other methods. The ordinate of
the resulting "free receptor" plot (e.g., figure 4-20) was the same as
that of the conventional Scatchard plot, but the abscissa was changed
from bound (Bsp) to free receptor concentration (BQ-Bsp) by subtracting
each value of Bsp from the corresponding value of Bq derived by
Scatchard analysis of the complete isotherm containing the input data
point. A line (which theoretically should satisfy the Scatchard
equation 4-4 and pass through the origin) was fit by 2-parameter
least-squares linear regression and thus was not constrained to
intersect the origin. The line was actually fit by a computerized

100
non-linear regression program (Helwig and Council, 1979) that generated
a standard error of the mean ("asymptotic" s.e.m.; Ralston and
Jennrich, 1978) for the merged estimate of the parameter K^, the
reciprocal of the slope of the "free receptor" plot. This unorthodox
s.e.m. was never used to derive an inferential statistic; however, it
did provide an estimate of the variability within the total pool of
data.
The estimate of Bq derived from the Scatchard plot for each
individual isotherm was also used, in conjunction with the individual
values of B , to construct the Hill plot for the particular experiment
according to the Hill equation
logit e = 1og[e/(1-e)] = n log (F/Kd), (4-5)
where e is the binding site occupancy (B^/Bq) and n, the exponent of F
in the basic isotherm equation B = BqF11/^ + Fn), is the Hill coef¬
ficient, which is 1.0 for a single class of noninteracting binding
sites. A line was fit by linear regression to the points whose
occupancy (e) did not exceed 80% (i.e., logit 0 i.0.6), and the slope of
this line was taken as the Hill coefficient. A slope significantly
different from 1 in the neighborhood of the x-axis of a Hill plot (where
logit 6 = 0) is indicative of apparent binding cooperativity or some
other, artifactual source of curvature in the initial Scatchard plot.
Although seldom used as such, the value of F at the x-intercept is an
estimate of the dissociation constant K,. Sometimes a number of
d
separate data sets from independent experiments were combined in a
"merged" Hill plot (e.g. figure 4-18), which consisted simply of a

101
superposition of the points from individual Hill plots constructed as
described above. From such a plot only data points corresponding to a
receptor occupancy (e) between 20% and 80% (-0.6 <_ logit e £ 0.6) were
included in the subsequent analysis. A curve was fit to the points by a
computerized cubic spline algorithm (cubic spline Fortran library
subroutine, International Mathematical and Statistical Library; see
Reinsch, 1967) that employs polynomials to smooth data in accordance
with a built-in statistical criterion (Craven and Wahba, 1979); this
method of regression contains no assumptions (other than the continuity
of the function and derivatives and smoothness criterion) restricting
the basic form or shape of the curve, and thus is appropriate for
empirically determining both the shape of the Hill plot and the abscissa
and slope at the 50% occupancy point (where logit e = 0). The slope of
the curve at the x-intercept (50% occupancy) was taken as the combined
Hill coefficient, and the value of F at this point provided a merged
estimate of K^. (The IMSL subroutine is unable to provide summary
statistics for these binding parameters.)
In order to verify that the binding parameters derived from a
least-squares linear regression fit to the points on a Scatchard plot
were not biased seriously (since the Scatchard coordinate system not
only has appreciable error in the independent variable, B , but also
unfortunately has correlated error in the independent and dependent
variables; for review see Rodbard, 1973) a standard computer program
(Helwig and Council, 1979) was used to fit some of the binding isotherms
by a weighted, nonlinear regression technique (Marquardt, 1963) using
the relatively error-free independent variable SL (total [ Hjligand).
The model to which the data were fit consisted of the sum of one

102
saturable high-affinity ("specific") component and one nonsaturable
("nonspecific") component, which allowed us to further check the
validity of the simple linear Scatchard method by omitting subtraction
of the 200X "nonspecific" correction. The binding model was the
following:
bt = BoF/(Kd+ F) + W- (4"6)
The actual regression equation (which is rather lengthy) was found by
substituting F = Sy - By into equation (4-6) and then solving the
resulting expression for By explicitly. This regression equation (not
shown) thus does not contain F; it accepts By and Sy as pairs of input
variables and then regresses By on the relatively error-free variable
Sy, fitting the adjustable binding parameters K^, Bq, and C-j (the
asymptotic "sink" of nonspecific binding). Each input data point was
2
weighted as 1/By , consistent with the assumption that the coefficient
of variation or percentage error in the measurement of By is constant
over the range of By. The resulting complete 3-parameter regression
model was then plotted in the Scatchard coordinate system for display
(e.g., figure 4-14), and each of the two components was also plotted
separately.
It would also be desirable to combine data sets from separate
isotherms in a merged, weighted nonlinear regression of By on the
relatively error-free variable Sy in a manner similar to that described
above for the simple linear "merged Scatchard" analysis. Each value of
By would be normalized by the appropriate protein concentration to the
units fmole/mg protein; the free (F) and total ligand concentration (Sy)

103
would remain in molar units (e.g., nM). The regression model
(equation 4-6) and the actual regression equation would be exactly the
same as described above, except that and Bq now would be expressed in
the units fmole/mg protein. The regression would provide estimates of
the parameters Bq, K^, and C-j; and the results of the merged regression
would be plotted for display in the same coordinate system as the
"merged Scatchard" plot described above. This analysis would also
require the assumption that the parameters to be fit do not vary with
the cytosol protein concentration.
Although the absence of a correlation between Bq (fmole/mg) and
cytosol concentration made the above assumption seem reasonable, the
variability of the individual estimates of receptor concentration (Bq)
again suggested that a better merged regression estimate of would be
obtained by performing the nonlinear regression with Bq as an input
variable, instead of using it as a unitary parameter to be estimated.
Therefore a 2-parameter, 3-variable regression was performed using
exactly the same regression model and equation (again weighted as 1/By )
as described above, except that for each value of By, the corresponding
estimate of Bq from a Scatchard analysis of the individual isotherm con¬
taining the input data point was used, in addition to the total ligand
concentration (S^), as a second (unweighted) independent variable. The
regression program thus generated estimated values of Kd and C-| and
their "asymptotic" standard errors described above. The resulting com¬
plete 2-parameter regression model was plotted for display (e.g., figure
4-16) in the "Scatchard-1ike" coordinate system in which By was replaced
by Bt/Bq, the normalized individual value of total bound steroid. The
measured nonspecific binding corrections (B^) were sometimes

104
incorporated into the above regression schemes based on equation (4-6)
by simply setting C-| = 0 and concomitantly replacing By with B$ . No
attempts were made to fit models containing two or more high-affinity,
saturable binding sites, since conventional Scatchard plots offered no
evidence of binding site heterogeneity.
In order to further examine binding isotherms for apparent "fine
structure" that might be indicative of heterogeneity or apparent
cooperativity, but that is not obvious from Scatchard or other simple
methods of analysis that assume a single class of noninteracting binding
sites, some isotherm data sets were transformed into continous affinity
distributions or spectra of equilibrium constants by the approximate
method of finite differences described by Hunston (1975) and by Thakur,
Munson, Hunston and Rodbard (1980). Because the approximate method of
finite differences generates a rather broad spectral line (instead of a
narrow spike or 6-function) even from "perfect" data derived from models
containing only a single class of noncooperative receptors, these
transformations of the experimental values of total binding (By) were
then compared with spectral transformations ("comparison spectra"
representating a single class of saturable, noninteracting binding
sites) of binding data (By) "predicted" by the 3-parameter nonlinear
regression model (described above) derived from the same set of
experimental data used to generate the "unconstrained" spectrum to be
analyzed. Thus, the comparison spectrum consists of a single broad
"line" having the minimum line width that can be "resolved" by the
finite differences method. Spectra A and B of figure 4-22 are
representative, respectively, of the comparison and unconstrained
spectra generated by transformation of the data from a single binding

105
isotherm. Both spectra of such a pair were generated by applying the
transformation to smoothed binding functions expressed in the log By -
log F coordinate system. To generate the comparison spectrum (A) the
previously-fit 3-parameter regression equation was transformed to the
log By - log F coordinate system before use of the finite differences
algorithm; thus, the binding data for the comparison spectrum were
"smoothed" by force-fit to a specific model containing only one
saturable binding site. The unconstrained spectrum (B) was produced by
smoothing the experimental By data in the same coordinate system with
the cubic spline subroutine before transformation to the affinity
distribution. Thus, to produce this spectrum the data were not
force-fit to any specific biophysical model such as equation (4-6).
For display the spectra were normalized by the total receptor concentra¬
tion (Bq) estimated by the 3-parameter nonlinear regression; thus, the
finite difference equation (equation 4 of Thakur et al., 1980, which
contains an error in the reference itself) takes the form
N(K) = - a(f2 - 2fy )/(a-l )2]/2BQ log a, (4-7)
where f-j and are as defined in Thakur et al. (1980). The input
spacing for the transformation Alog K = 0.1, and log a = 0.2. The
dimensionality of K is M""* (1/mole); the normalized N(K) itself is
dimensionless. The peak of the comparison spectrum is located at
(-log K^) on the abscissa, where is the estimate derived from the
3-parameter nonlinear regression.
Data sets from separate isotherms were also combined to generate
pairs of "merged" affinity spectra (e.g., figure 4-24) following the

106
normalization of each value of Bj by the corresponding estimate of Bq
derived from a Scatchard analysis of the individual isotherm containing
the input data point. In this analysis the comparison spectrum (A) is a
transformation of normalized total binding data (Bj/Bq) "predicted" by
the merged 2-parameter nonlinear regression model (in which Bq is an
input variable, described above) derived from the same set of
experimental data. Both spectra of such a pair were generated by
applying the transformation to smoothed binding functions expressed in
the log (Bj/Bq) - log F coordinate system; the unconstrained spectrum
(B) was produced by smoothing the normalized experimental data (Bj/Bq)
in the same coordinate system with the cubic spline subroutine before
transformation to the affinity distribution as described above. In the
merged analysis the values of f-j and f^ are dimensionless (since Bj/Bq
is dimensionless) and hence Bq does not appear in equation (4-7) when it
is used for the merged analysis.
The binding selectivity or specificity of the putative
glucocorticoid receptors was explored by measuring the affinity of
3
several different unlabeled steroids for the saturable [ H]dexamethasone
3
binding sites. Isotherms were generated with [ Hjdexamethasone as
described above, first in the absence and then (using the same pool of
cytosol) in the presence of a fixed total concentration of the unlabeled
competitive inhibitor whose dissociation constant was to be estimated
(e.g., figure 4-27). The data resulting from this "Edsall - Wyman"
experimental design were analyzed by two different methods. The
equilibrium dissociation constant K^. for the competitive ligand was
first calculated by making the assumption that the concentration of free
(unbound) competitor (Fq) was equal to the total concentration present

107
in the tubes (Sg), and therefore constant over the range of labeled
ligand concentration. The effect of a constant concentration of free
competitor on a Scatchard plot describing the binding of a labeled
ligand to a single class of noncooperative binding sites is given by the
Edsall - Wyman equation (e.g., Cantor and Schimmel, 1980), which can be
rearranged to the convenient Scatchard form given by equation (3-3) and
restated here as
bl/fl = -(bl - V/Kd(1 + Fc/KdiJ» (4_8)
where the subscript L refers to [ H]dexamethasone. Thus, the Edsall -
Wyman equation predicts simply that the slope of the Scatchard plot will
be reduced by the factor 1/(1 + Fg/K^..) in the presence of a constant
concentration of free inhibitor F^.; the estimate of K^. was calculated
directly from the slopes (estimated by linear regression) of the two
Scatchard plots and the total concentration of the inhibitor. However,
since the high-affinity competing steroids were not present in great
excess over the total concentration of binding sites (Bg), the approxi¬
mation underlying use of the Edsall - Wyman equation to calculate K^.
had to be questioned (see chapter III). If the competitive inhibitor
is not present in considerable excess over Bg this approximation will
not be valid, the resulting Scatchard plot will be curved (which may not
be apparent by visual inspection of the points), and the error in the
calculated Kdi may be substantial.
For this reason a simple and mathematically correct procedure that
does not require this assumption was also used to calculate the K^.
values for the competing steroids. At equilibrium the mass action rate

equations for the binding of the labelled ligand and the competing
steroid may be written as
108
(Bq - Bl - Bc)Fl = KdBL and
(4-9)
(4-10)
where subscripts L and C refer, respectively, to the labeled and
competing ligands. This suggests immediately the following
Scatchard-1ike "free receptor" plot (e.g., figure 4-27) described by the
equation
(4-11)
where the bound/free ratio now refers to the competing ligand C. Since
Bq and had already been determined from the initial Scatchard plot
constructed in the absence of the competitive inhibitor, equation (4-9)
was used to calculate the abscissa [(Bq - Bq - Bq), free binding sites]
of the "free receptor" plot described by equation (4-11). The ordinate,
Bq/Fq, was calculated with the aid of equation (4-9) in combination with
the simple identity Fq = Sq - Bq (i.e., the "nonspecific" binding of
competitor C was neglected). A line (which theoretically should satisfy
equation 4-11 and pass through the origin) was fit by 2-parameter
least-squares linear regression and thus for statistical reasons was not
constrained by the analysis to intersect the origin. Since the
competition "free receptor" plot estimates only one binding parameter
(Kdi-), data from independent experiments employing different cytosol

109
concentrations and different concentrations of the competing steroid
were also merged directly for analysis without further scaling or
modification; in such a procedure the nonlinear regression program was
again used to generate a standard error (s.e.m.) for the resulting
estimate of Kdi-, the reciprocal of the slope of the "free receptor"
competition plot. Values of calculated by the two different methods
were compared.
Results
Efficiency and Linearity of the DEAE Filter Assay
The efficiency of an assay refers to the probability that a
specific hormone-receptor complex will be detected by the assay, i.e.,
the probability that the complex will remain bound to the filter paper
and that the [ H]steroid will not dissociate during washing of the free
steroid from the filter (Yarus and Berg, 1970). The efficiency of the
DEAE filter assay was determined both by titration of a fixed low
concentration of [ Hjdexamethasone with receptors in increasing concen¬
trations of cytosol protein (suggested by Santi et al., 1973) and by
comparison with a simple gel filtration assay whose efficiency was
assumed to be 100%; figure 4-1 depicts both methods. In the first
method concentrated cytosol was diluted with buffer A to a series of
lower concentrations (1:3/4:1/2:1/3:1/4:...1/8). Pairs of samples
(250 ul each tube) at each protein concentration were incubated at 2°C
for 24 h with a low concentration (approximately 5 x 10"^M) of
3
[ Hjdexamethasone and (for one of each sample pair) a 200-fold excess of
unlabeled dexamethasone. The tubes were assayed in triplicate by the
DEAE filter assay, and the resulting measured values of specific binding

110
(B ) were extrapolated (in the Scatchard-1ike coordinate system of
figure 4-1, which assumes that receptor occupancy is low) by linear
regression to infinite protein (and hence receptor) concentration. The
ratio of the projected x-intercept of the plot to the concentration of
[ Hjdexamethasone actually present in the incubation provided an
estimate of the assay efficiency; this procedure assumed that the
functional receptor concentration was linear with protein concentration
(see below and figure 4-26) and that the assay itself was linear with
protein concentration (i.e., had constant efficiency) within the range
of protein concentration employed (see below). The method yielded an
efficiency estimate of 76% ± 2% (n=3); at all protein concentrations the
nonspecific corrections were very low and had little effect on the final
estimate of the efficiency.
The efficiency of the filter assay was also determined by direct
comparison with gel filtration and dextran-charcoal (DCC) assays
performed with the same cytosol samples at diffferent protein
Q
concentrations (inset to figure 1). Following incubation with 2 x 10"
M [ Hjdexamethasone (with and without unlabeled dexamethasone) pairs of
cytosol samples were assayed (as 50 yl triplicates) for specific binding
(B ) by the DEAE assay, by filtration on Sephadex G-25 minicolumns, or
sp
by adsorption of free steroid onto dextran-coated charcoal as described
in Methods. In agreement with the efficiency determined by titration
with increasingly concentrated cytosol samples, the DEAE filter assay
measured 76 ± 3% (n=3 experiments) of the specific binding detected by
the G-25 minicolumn assay (assumed arbitrarily to possess 100%
efficiency); this ratio was not dependent upon protein concentration.

Fig. 4-1. Determination of the efficiency of the DEAE filter assay by titration of a
fixed concentration of [JH]dexamethasone with glucocorticoid receptors in
increasing concentrations of cytosol protein.
The ratio of the projected x-intercept of the "Scatchard-1ike" plot to the concentration
of [ Hjdexamethasone actually present in the incubation provides an estimate of the assay
efficiency. The depicted protein concentrations ranged from 1.5 to 8.9 mg/ml, and the
o
constant [ Hjdexamethasone concentration was 0.58 nM. For the particular experiment shown
above the efficiency estimate was 72%. Inset: determination of the efficiency (relative
to the Sephadex G-25 filtration assay) of the DEAE filter assay and of the dextran-coated
charcoal assay at different cytosol protein concentrations. The relative efficiencies
plotted above are x ± s.e.m. for 3 independent determinations at a constant
O Q
[ Hjdexamethasone concentration (2 x 10 M). The DEAE assay efficiency (•) is not
affected by protein concentration in the range depicted above, but that of the
dextran-charcoal assay (A) is strongly dependent on the cytosol concentration.

Bsp/[pYT0S0L PROTEIN] (pM- ml/mg protein)
(pM)

113
The efficiency of the charcoal (DCC) assay (85% relative to the gel for
filtration column assay at the highest protein concentration, decreasing
to approximately 30% at the lowest) was strongly dependent on protein
concentration, apparently because the samples were diluted 20:1 by the
assay conditions; this reduction of the DCC assay efficiency caused by
receptor adsorption to the charcoal at low protein concentrations has
often been observed (e.g., Katzenellenbogen, Johnson and Carlson, 1973).
Thus, for all subsequent determinations of affinity and binding capacity
the efficiency of the DEAE filter assay was taken to be 76%; this value
is essentially equivalent to the efficiency reported for a similar assay
for serum sex steroid binding protein (Mickelson and Petra, 1974) and is
somewhat lower than the 86% efficiency reported for hepatoma cell (HTC)
glucocorticoid receptors (Santi et al., 1973). The efficiency of such
ion-exchange filter assays depends upon the macromolecular species to be
measured and upon the pH, ionic strength, and composition of the buffer.
Figure 4-2 displays the linearity of the DEAE filter assay explored
as a function of the amount of cytosol protein applied to the filters.
Pairs of cytosol samples equilibrated with 2 x 10 M [ H]dexamethasone
and (for one of each sample pair) a 200-fold excess of unlabeled
dexamethasone were diluted rapidly to the desired protein concentration,
and 50 yl samples were assayed in triplicate for the determination of
specific binding (B^). The assay was linear in the range explored,
which extended from 50 to 600 ug cytosol protein per filter
(corresponding to cytosol protein concentrations ranging from 1-12
mg/ml); the similar assay described by Santi et al. (1973) is linear in
the range extending from 0-4000 yg protein/filter (corresponding to

3
Fig. 4-2. Linearity of the retention of [ Hjdexamethasone-receptor complexes by DEAE
filters as a function of the amount of cytosol protein applied.
-8
Samples incubated with 2 x 10” M dexamethasone were diluted in rapid serial fashion and
50 ul aliquots were filtered in triplicate. Upper curve: specifically bound steroid.
Lower curve: nonspecifically bound steroid defined by incubation of the cytosol with
3
[ Hjdexamethasone and a 200-fold excess of unlabeled steroid before dilution and
filtration. The undiluted protein concentration was 10.8 mg/ml, and the receptor
concentration (Bq) was 357 fmole/mg protein. The experiment was repeated 3 times with the
same resulting linearity of the specific binding.

en
fj.q CYTOSOL PROTEIN / DEAE FILTER DISC

116
cytosol protein concentrations ranging from 0-80 mg/ml). The experiment
was repeated (n=3) with the same result.
Effects of Medium Composition and Temperature on In Vitro Receptor
Stab i 1ity
In order to minimize the loss of functional binding sites during
cytosol preparation and lengthy incubations, we examined the effect of
varying the pH, the concentration of the sulfhydryl-protective reagent
dithiothreitol (DTT), and the concentration of sodium molybdate
(^MoO^) on the specific [ Hjdexamethasone binding capacity (B )
assayed at high receptor occupancy (near saturation); the other
components of buffer A were not varied. Specific [ Hjdexamethasone
binding capacity remained constant within the pH range from 7.0 to 8.2
that was explored (not shown), and buffer adjusted to pH 7.6 was used
for all further experiments. (Depending upon the tissuerbuffer ratio,
the pH of cytosol can be .1-.2 pH units lower than the pH of the
homogenization buffer.)
The strong effect of dithiothreitol (DTT) on the in vitro stability
of glucocorticoid receptor steroid binding sites is shown in figure 4-3.
Cytosol was prepared in the buffer A (without DTT), and pairs of samples
were adjusted to the different DTT concentrations with a concentrated
DTT stock solution (containing the other buffer A ingredients) and
additional buffer A. Following 12 hours of incubation without steroid
("aging") at 2 C the samples were incubated for 12 h at 2 C with 2 x
10 M [Hjdexamethasone and excess "cold" dexamethasone (one of each
pair). 50 yl aliquots were then assayed in triplicate with the DEAE
filter assay for the determination of specific binding (B^).
Essentially all functional binding sites were lost in the absence of

Fig. 4-3. Effect of dithiothreitol (DTT) concentration on the stability of mouse brain
glucocorticoid receptors.
Cytosol was prepared in buffer A (without DTT), and pairs of samples were adjusted to the
different DTT concentrations with a concentrated DTT stock solution (containing the other
buffer A ingredients) and additional buffer A. Following 12 hours of "aging" without
steroid at 2°C the samples were incubated for 12 h at 2°C with 2 x 10"®M [^Hjdexamethasone
and excess "cold" dexamethasone (one of each pair). 50 yl aliquots were assayed in
triplicate with the DEAE filter method for the determination of specific binding. The
final cytosol protein concentration was 4.1 mg/ml. The "plateau" receptor concentration
(mean of determinations at 4 highest DTT concentrations) was 300 fmole/mg cytosol protein.

1.50
Bsp
(nM)
[du] (mM)
025
1.0
2.0

119
DTT, and the measured plateau receptor concentration was achieved with
0.5-0.75 mM DTT; subsequent experiments were performed with 2 mM DTT to
prevent the oxidation of sulfhydryl groups that affect the conformation
of the steroid binding sites. Other investigations of glucocorticoid
receptors from a variety of tissues have shown that the loss of
functional binding sites in the absence of DTT occurs during the period
of cytosol "aging" without steroid; formation of the
glucocorticoid-receptor complex stabilizes the receptor sulfhydryl
groups and prevents their oxidation and the subsequent further loss of
functional binding sites in the absence of DTT (e.g., Granberg and
Ballard, 1977).
The large effect of molybdate (MoO^) ion on the in vitro stability
of glucocorticoid binding sites is shown in figure 4-4. Cytosol was
prepared in buffer A (without Na^MoO^), and pairs of samples were
adjusted to the different NagMoO^ concentrations with a concentrated
Na^MoO^ stock solution (containing the other buffer A ingredients) and
additional buffer A. Following 12 hours of "aging" without steroid at
2°C or at 22°C the sample pairs were incubated for 12 h at 2°C with
2 x 10' M [ Hjdexamethasone and excess unlabeled steroid (one of each
pair). 50 yl aliquots were assayed in triplicate with the DEAE filter
assay for the determination of specific binding (Bsp). Cytosol
incubated for 12 h at 2°C without steroid required only 1-2 mM Na^MoO^
(perhaps less) for prevention of the loss of functional binding sites
("decapacitation"). In contrast, essentially all sites were lost at
room temperature in the absence of molybdate, and attainment of the
measured plateau receptor concentration required approximately 8 mM
^MoO^ for full protection from heat inactivation. Figure 4-4 also

120
shows (inset) that the 10 mM Na^MoO^ contained in buffer A is fully
protective of unoccupied binding sites during low-temperature
incubations lasting as long as 24 h, a condition that is necessary for
the construction of meaningful binding isotherms with ligands that
require long incubations for the attainment of equilibrium. The heat-
accelerated inactivation of binding sites ("decapitation") and the
protective effect of the concentration of molybdate chosen for buffer A
(10 mM) were studied further in relation to the time and temperature of
the "aging" incubations (without steroid). Cytosol was prepared in
buffer A (figure 4-5, upper panel) or buffer A without molybdate (lower
panel). Following a variable period of "aging" without steroid at 2°C,
12°C, 22°C or 32°C the concentration of functional binding sites
remaining in the cytosol was assayed as described above. In the absence
of molybdate the unoccupied receptor pool was inactivated at 2°C with a
half-life (tA) of about 10 hours; at 12°C the t^ decreased to
approximately 1 h, and at room temperature (22°C) and above the loss of
sites (decapitation) was very rapid. (In the experiment shown in figure
4-5 the rate of decapacitation at 2°C in the absence of molybdate was
slightly faster than the rate suggested by the initial point on the 2°C
curve of figure 4-4). Consistent with the results presented in
figure 4-4 and described above, the molybdate concentration of buffer A
(10 mM) was fully protective for at least 10 h, except at the highest,
32°C "aging" temperature. (All known steroid receptors are unstable at
such high, relatively "physiological" temperatures under all in vitro
conditions that have yet been explored.)
The protective effect of molybdate on unoccupied mouse brain gluco¬
corticoid binding sites indicated by the data of figures 4-4 and 4-5 is

Fig. 4-4. Effect of molybdate concentration on the stability of mouse brain
glucocorticoid receptors.
Cytosol was prepared in buffer A (without Na^MoO^), and pairs of samples were adjusted to
the different ^MoO^ concentrations with a concentrated Na^MoO^ stock solution
(containing the other buffer A ingredients) and additional buffer A. Following 12 hours
of "aging" without steroid at 2°C ( ) or at 22°C ( ) the samples were incubated for 12 h
at 2°C with 2 x 10 M [ Hjdexamethasone and excess unlabeled steroid (one of each pair).
50 yl aliquots were assayed in triplicate by the DEAE filter method for the determination
of specific binding. Because two completely independent experiments were depicted, each
value of specific binding (B ) has been normalized by the "plateau" level of B for the
★ sp sp
particular experiment (Bq, the mean of the determinations at the 4 highest molybdate
concentrations). The final cytosol protein concentrations were 5.6 mg/ml for the 2°C
experiment and 4.7 mg/ml for the 22°C experiment. The "plateau" receptor concentrations
were 240 fmole/mg protein (2°C) and 380 fmole/mg protein (22°C). Inset: stability of
unoccupied mouse brain glucocorticoid receptors at 2°C in buffer A (containing lOmM
Na^MoO^). Cytosol was prepared in buffer A and assayed for specific binding as described
above after the variable "aging" period. The origin (0) of the time axis corresponds to
the end of the 90 min cytosol preparation period when the first samples were labeled with
3
[ Hjdexamethasone. The values displayed are x ± s.e.m. for 3 independent experiments.
Cytosol protein concentration was 7 mg/ml, and the mean receptor concentration was
330 fmole/mg cytosol protein.

l.2-i
1.0-
0.8-
0.6-
0.4-
0.2
[Nq^ M0O4]
4
5
10 15 20
AGING TIME (HRS)
(mM)

Fig. 4-5. Inactivation of mouse brain glucocorticoid receptor binding
sites ("decapacitation") as a function of time, temperature,
and the presence or absence of lOmM Na^MoO^.
Cytosol was prepared in buffer A (upper panel) or buffer A without
molybdate (lower panel). Following a variable period of "aging" without
steriod at 2°C, 12°C, 22°C or 32°C the pairs of samples were incubated
for 6 h at 2°C with 1 x 10-^ M [^H]dexamethasone and excess (200X)
unlabeled steroid (one of each pair). 50 ul aliquots were assayed in
triplicate with the DEAE filter assay for the determination of specific
binding. Because experiments using two independent pools of cytosol are
depicted, each value of specific binding (B ) has been normalized by
the initial measured value of B for the particular pool of cytosol.
The origin of the time axis corresponds to the end of the 90 min cytosol
preparation period. Cytosol protein concentrations were 3.1 mg/ml
(upper panel) and 3.2 mg/ml (lower panel); initial values of B were
270 fmole/mg protein (upper panel) and 310 fmole/mg protein (lower
panel). The molybdate concentration of buffer A (10 mM) is fully
protective for at least 10 h, except at the highest aging temperature
(32°C).

(% OF 0 HR.)
124

125
consistent with reports of similar results from studies with
glucocorticoid receptors from a variety of other sources (e.g., Nielsen,
Sando and Pratt, 1977; Leach, Dahmer, Hammond, Sando and Pratt, 1979);
actual rates of heat-induced glucocorticoid receptor decapacitation in
the absence of molybdate vary with tissue source and cell type as well
as with cytosol concentration, possibly because different preparations
possess different concentrations of relevant endogenous factors in
addition to the receptors themselves.
The molybdate concentration of buffer A (10 mM) has also been
reported to completely block the activation (nucleophilic
transformation) of glucocorticoid receptors from a variety of tissues
(e.g., Leach et al., 1979; Dahmer, Quasney, Bissen and Pratt, 1981),
permitting the measurement of kinetic and equilibrium binding parameters
characteristic of a single homogeneous pool of receptors (i.e.,
non-activated, albeit probably influenced by the presence of molybdate).
Furthermore, the results of DEAE mini column chromatography performed as
described in Methods suggested that the activation of mouse brain gluco¬
corticoid receptors incubated in cold buffer A was negligible.
Consistent with similar results from studies of nonactivated receptors
from other sources (e.g., Vedeckis, 1981), a single peak of bound
3
[ H]TA was eluted at the ionic strength corresponding to
buffer A + 160 mM KC1 (not shown), indicating that the entire receptor
population remained in the more acidic, nonactivated form. The
mechanisms by which molybdate exerts its protective effect on steroid
binding sites and prevents nucleophilic receptor transformation (acti¬
vation) are, however, mysterious; these are currently subjects of
intense investigation. Current speculations include both direct

126
molybdate-receptor interactions and indirect influences mediated by
effects of molybdate on other endogenous modulators, such as the enzymes
of a phosphorylation-dephosphorylation cycle (e.g., Grody, Schrader and
O'Malley, 1982, for review).
Equilibrium Binding Characteristics of the Mouse Brain Glucocorticoid
Receptors
In addition to the necessary demonstration of a saturable
population of high-affinity binding sites having specificity for
glucocorticoid agonists and antagonists, some important aspects of the
characterization of the receptors are: 1) confirmation that the binding
sites are highly selective for a specific molecular shape
(sterospecificity), 2) the determination of the subcellular distribution
of the binding sites, and 3) confirmation of the chemical identity of
the ligand actually bound in the hormorie-receptor complex under
investigation.
Figure 4-6 reveals a high degree of stereospecificity in the
glucocorticoid-receptor interaction that was demonstrated by comparing
the inhibitory potencies of the diastereomers cortisol (llg-F) and
epicortisol (lla-F, a non-glucocorticoid) as competitive inhibitors of
the binding of [ Hjdexamethasone. Cytosol was prepared in buffer A, and
pairs of samples were adjusted to the indicated concentrations of
cortisol or epicortisol. The pairs of samples were then incubated for
16 h at 2°C with 6 nM [^Hjdexamethasone and 200-fold excess cold
dexamethasone (one of each pair). 50 ul aliquots were assayed in
triplicate with the DEAE filter assay for the determination of specific
binding. As expected, only cortisol (the 11B-0H compound) was an
effective competitor for the [ Hjdexamethasone binding sites, indicating

Fig. 4-6. Stereospecificity of steroid binding to mouse brain glucocorticoid receptors
labelled with [^Hldexamethasone.
Cytosol was prepared in buffer A, and pairs of samples were adjusted to the indicated
concentrations of the diastereomers cortisol (113-F,#) or epicortisol (lla-F,A ). The
pairs of samples were then incubated for 16 h at 2°C with 6 nM [ Hjdexamethasone and excess
(200X) cold dexamethasone (one of each pair). 50 ul aliquots were assayed in triplicate
with the DEAE filter assay for the determination of specific binding. The values of
specific binding have been normalized by the level of specific binding measured in the
absence of competing cortisol or epicortisol (1.4 nM or 230 fmole/mg protein). Cytosol
protein concentration was 5.9 mg/ml. Only the 116-OH compound was an effective competitor
3
for the [ Hjdexamethasone binding sites.

100
80
60
40
20
A
8 7
Log [STEROID]
PO
00

129
the importance of the ligand shape determined by the spatial arrangement
of the functional groups on the steroid nucleus; the 1 IB-OH is an
absolute requirement for glucocorticoid activity.
Subcellular fractionation (in buffer A, a hypertonic medium) into
nuclear, crude mitochondrial, microsomal and cytosol components revealed
that essentially all high-affinity [ H]dexamethasone binding sites
(assayed at 2 x 10 M [ Hjdexamethasone) were released into the high¬
speed supernatant following homogenization in buffer A; the subcellular
distribution of unoccupied binding sites in vivo is not known.
Dexamethasone does not undergo metabolic transformation; the
extremely remote possibility that the endogenous corticosterone requires
metabolic activation before binding to the receptors was eliminated by
checking the chemical identity of radioactivity recovered from the DEAE
filters following the assay of cytosol labeled with [ H]corticosterone.
All radioactivity recovered from the filters was indistinguishable from
3
authentic [ Hjcorticosterone by the LH-20 chromatographic separation
described by Sippell et al. (1975).
Equilibrium isotherms constructed with increasing concentrations
3 3
of [ Hjdexamethasone (e.g., figure 4-7), [ H]TA (not shown), and
3
[ Hjcorticosterone (e.g., figure 4-8) revealed saturable populations of
high-affinity binding sites. The apparent affinities for the three
ligands were, however, quite different; and the concentration of binding
sites for [ Hjcorticosterone was significantly greater than the approxi-
mately equal concentrations of [ Hjdexamethasone and [ HjTA binding
sites. The saturation isotherms all approximated rectangular
hyperbolas, suggesting that each ligand was apparently interacting with
a single population of saturable, high-affinity receptors. No evidence

3
Fig. 4-7. Representative equilibrium isotherm for the binding of [ H]dexamethasone to
glucocorticoid receptors in perfused mouse brain cytosol.
Cytosol was prepared in buffer A, and 15 pairs of samples (250 vl) were incubated for 24 h
at 2°C with increasing concentrations of [ H]dexamethasone and, for one of each sample
pair, a 200-fold excess of unlabeled steroid. 50 ul aliquots were than assayed in
triplicate by the DEAE filter method for the determination of total binding (By,®) and
nonspecific binding (B^»A). Specifically bound steriod (BSp,#) was determined by
substracting B^ from B^. The concentration of free steroid (F) is plotted on the x-axis.
For the specific experiment depicted above the cytosol protein concentration was 6.6 mg/ml
3
and the total [ H]dexamethasone concentration ranged from 0.06 to 420 nM (the two
3
determinations at total [ Hjdexamethasone concentrations above 25 nM are not shown).

B(nM
F (nM)
OJ

3
Fig. 4-8. Representative equilibrium isotherm for the binding of [ Hjcorticosterone to the
complete ensemble of saturable high-affinity binding sites in perfused mouse
brain cytosol.
Cytosol was prepared in buffer A, and pairs of samples (250 yl) were incubated for 16 h at
3
2°C with increasing concentrations of [ Hjcorticosterone and, for one of each sample pair,
a 200-fold excess of unlabeled corticosterone. 50 yl aliquots were then assayed in
triplicate by the DEAE filter method for the determination of total binding (By,B) and
nonspecific binding (B^<.,A). Specifically bound steroid (B^,#) was determined by
subtracting B^<. from By. The concentration of free steroid (F) is plotted on the x-axis.
For the specific experiment depicted the cytosol protein concentration was 7.0 mg/ml and
3
the total [ H]corticosterone concentration ranged from 0.3 nM to 2800 nM (one measurement
3
at highest [ H]corticosterone concentration not shown).

B (n M )
50
(nM)

134
for secondary populations of saturable, lower-affinity binding sites was
observed when the [ Hjligand concentrations were increased at least two
orders of magnitude above the apparent Kd for the high-affinity sites.
The nonspecific binding component (B^^) continued to increase approxi-
mately linearly as the [ H]ligand concentrations were increased. For
each ligand the signal/noise (Bsp/BNS) ratio was excellent when
3
[ Hjsteroid concentrations did not greatly exceed amounts required for
near-saturation. For each ligand the data were superficially compatible
with a model consisting of one class of noninteracting, saturable sites
and a nonsaturable, approximately linear nonspecific component. The
data were analyzed by the transformations (e.g., Scatchard) and
regression schemes described above in Methods.
The problem of choosing appropriate incubation times for the
isotherm experiments required detailed analysis. Estimates of the time
3
required to reach equilibrium at the low [ H]dexamethasone
concentrations were obtained both by direct experimental observations
and also indirectly from a theoretical simulation of the rate of
approach to equilibrium calculated from the measured values of the
3
[ H]dexamethasone association and dissociation rate constants (to be
presented and discussed in chapter VI) and an assumed, "typical" value
of the binding site concentration. Disappointingly, the observed and
"theoretical" estimates of the required incubation times were not in
close agreement. Thus, before presenting the measured equilibrium
binding parameters we must digress to discuss the problem of the choice
of an adequate incubation time. The information presented in chapter II
will serve as background for the following description of the simulation
of the time course of [ H]dexamethasone binding.

135
The simulated approach to equilibrium is depicted in figure 4-9,
which presents the fraction of the equilibrium value of specific binding
attained as a function of the time of incubation, with the total
3
[ Hjdexamethasone concentration shown as the parameter. The calculation
3
required the mean values of the measured [ Hjdexamethasone association
and dissociation rate constants (described in chapter VI) as inputs to
the previously-discussed equations (2-5) and 2-13). The assumed
"typical" cytosol binding site concentration (Bg) was 3.2 mM (Bg ranged
from 2.1 to 3.9 mM in the dexamethasone isotherm experiments), and the
mean measured values of the association and dissociation rate constants
assumed for the calculation were k = 0.69 x 10^ M“* min-1 and
a
= 3.4 x 10“4 min-1 (see chapter VI). Figure 4-9 also presents (left
inset) a simulation of the relative deviation from equilibrium (e) of
o
specific binding (B ) plotted as a function of the total [ Hj¬
dexamethasone concentration, with incubation time as the indicated
parameter. The same rate constants and receptor concentration (listed
above) were input to equation (2-28) to generate the relative error (e)
curves; for this specific simulation the curves have maxima in the low
nanomolar range and actually decrease to approach constant values as the
steroid concentration is reduced. Thus, if an incubation time is chosen
such that the deviation from equlibrium (relative error e) is reduced to
an acceptable level for the samples incubated with 1 nM [ Hjdexametha¬
sone, then samples incubated with even lower concentrations of
[ Hjdexamethasone may also be used to generate the isotherm, since they
will attain at least as close fractional approaches to equilibrium in
the given time. Finally, figure 4-9 (right inset) presents the

Fig. 4-9. Simulated approach to equilibrium of specifically bound steroid (for a
representative set of incubations of ['3H]dexamethasone with glucocorticoid
receptors in perfused mouse brain cytosol) as a function of time and total
ligand concentration.
The fraction of the final equilibrium value attained is plotted on the ordinate as a
function of time after mixing, with total steroid concentration as the indicated parameter.
The simulation was performed by using the mean values of the measured steroid association
and dissociation rate constants (described in chapter VI) as inputs to equations (2-5) and
(2-13). The assumed binding site concentration (Bq) was 3.2 nM, the mean generated by
16 individual isotherms whose values of Bq ranged from 2.1 to 3.9 nM. The mean measured
values of the association and dissociation rate constants assumed for this simulation were
ka = 0.69 x 10^M"*min"* and = 3.4 x lO'^min-''' (see chapter VI). Left inset: Relative
deviation from equilibrium (e) of specific binding (B ) as a function of total
3
[ Hjdexamethasone concentration (abscissa), with incubation time as the indicated
parameter. The rate constants and receptor concentration listed above were input to
equation (2-28) to generate the relative error (e) curves; these curves have maxima in the
low nanomolar range and actually decrease to approach constant values as the steroid
concentration is reduced indefinitely. Right inset: The effect of inadequate incubation
times on the slopes of Scatchard plots derived from "equilibrium" binding isotherms. The
binding parameters (rate constants and receptor concentration) listed above were input to
equation (2-13) to generate the values of B^ for each indicated incubation time at the
seven different steroid concentrations (.5-50 nM). The lines were fit to the resulting
points by simple linear regression. The curvature in the simulated data is concentrated in
the region near the x-intercept and is not readily apparent upon visual inspection; it is
obvious that the apparent linearity of a Scatchard plot is not an adequate criterion for
the attainment of equilibrium.

TIME (HRS)
co

138
simulated effect of inadequate incubation time on the slope of the
Scatchard plot derived from a "non-equilibrium" binding isotherm. The
same binding parameters (rate constants and receptor concentration,
listed above) were input to equation (2-13) to generate the values of
B for each indicated incubation time at the seven different
sp
[ Hjdexamethasone concentrations (0.5-50 nM) used in the simulated
"typical" experiment. The lines were fit to the resulting points in
Scatchard space by least-squares linear regression. The curvature in
the simulated "nonequilibrium" Scatchard plots is concentrated near the
x-intercept; it is not immediately apparent upon visual inspection and
does not lead to greatly inflated Hill coefficients. It is thus obvious
that this superficial, apparent linearity, which could be masked easily
by experimental variance, is not an adequate criterion for the
attainment of equilibrium.
The above simulation suggested that our "typical" experiment with
3
[ Hjdexamethasone might require a rather lengthy incubation (perhaps
30-36 h), if the affinity was actually as high as the measured rate
constants indicated. For example, figure 4-9 (right inset) predicts
that a 16 h experiment analyzed by the routine linear Scatchard method
might overestimate the true by a factor of approximately 2. Thus, in
several experiments we measured specific [ Hjdexamethasone binding (BSp)
as a function of the time of incubation of cytosol (4 mg/ml) with 1 nM
3
[ Hjdexamethasone (the DEAE filter assay was as described above; data
not shown). Binding assays were performed after 12, 16, 20, 24 and 40 h
incubation with steroid at 2°C; no increase in B (which reached
sp
approximately 0.6 nM) was found beyond 12 h of incubation, and the
3
binding of [ Hjdexamethasone remained unchanged at 40 h. Furthermore,

139
several isotherms derived from experiments incubated beyond 24 h (up to
36 h) did not yield higher estimates of [ Hjdexamethasone affinity than
experiments whose incubations were terminated after 16 h. Consequently,
equilibrium incubations of cytosol with [ H]dexamethasone were
terminated after 16-24 h, in order to minimize the possible slow
decapacitation of steroid binding sites that might occur in vitro during
very prolonged experiments. A similar prediction based on the measured
association and dissociation rate constants for [ H]TA (described in
chapter VI) indicated that considerably longer incubations (50-100 h)
might be required for the attainment of equilibrium at the lower [ H]TA
concentrations used in a typical isotherm experiment (see also Gray and
Luttge, 1982); a duration of 48 h was chosen for the [ H]TA experimental
incubations, and specific binding was not observed to increase beyond
this time. The choice of incubation time for [ Hjcorticosterone
isotherms was not a problem; both simulation (based again on measured
rate constants) and observations indicated that specific binding
attained a steady state well before the 16-24 h incubations were
terminated.
The results of representative individual equilibrium isotherm
experiments conducted with the three [ H]glucocorticoid ligands, and
some results from merged analyses in which several isotherms were
combined, are presented in figures 4-10 through 4-25. Summary results
with standard errors for equilibrium binding parameters measured with
the three [ Hjligands are presented in table 4-1. Figure 4-10 (derived
from the specific binding data of figure 4-7) and figure 4-11 are
conventional Scatchard plots depicting the specific binding of

Table 4-1. Equilibrium binding parameters for tritiated glucocorticoids in perfused mouse brain
cytosol. The same experimental data (with the indicated exception) have been analyzed by the
different methods discussed in the text and in chapter III. The tabulated parameter estimates are
either x ± s.e.m. or individual determinations. Numbers within parentheses indicate either units
of measure or the number of independent experiments that are averaged or merged. Steroid trivial name
abbreviations are defined in the footnotes to table 4-2.
Parameter Method9
[3H]DEX + DEX(200X)
[3H]TA + TA(200X)
[3H]B + DEX(200X)
[3H]B + B(200X)
Kd
(xlCf 9M)
(xl0-10M)
(xl0"9M)
(xl0”9M)
A
1.79 ± 0.24
08)
2.80 ± 0.43 (3)
7.55 ± 0.58 (3)
6.81 ± 0.60 (7)
B
1.69 ± 0.08
( 3)
—
—
—
C
1.79 ± 0.09b
(18)
—
—
6.65 ± 0.27b (7)
D
1.90 Í 0. 09b
(18)
—
—
7.06 ± 0.26b (7)
E
1.54 ± 0.11b
(18)
—
—
7.04 ± 0.04b (7)
F
CO
o
C\J
—
—
6.18C (7)
Continued
-p*
o

Table 4-1. (Continued)
Parameter
Method3 [3H]DEX + DEX(200X) [3H]TA + TA(200X)
[3H]B + DEX(200X)
[3H]B + B(200X)
Kd
(x10"9M)
X
o
1
o
2
(x10"9M)
(x10"9M)
G
1.74 (18)
—
—
4.57 (7)
H
0.46 ± 0.07 (3)
0.34 (1)
9.52 ± 1.06 (3)
—
Hill "n"
I
1.01 ± 0.03 (15)
1.04 ± 0.08 (3) 1.01 ± 0.02 (3)
0.95 ± 0.03 (7)
F
0.99d (18)
—
—
0.95d (7)
B0 or bmax
(fmol e/mg protein)
(fmole/mg protein)
(fmole/mg protein)
(fmole/mg protein)
A
374 ± 15 (43)e
397 ± 32 (3)
364 ± 59 (3)
602 ± 36 (15)f
a. Methods used for the analysis of binding data are A: individual Scatchard plots (B input, simple
linear regression); B: individual Scatchard plots (constant ligand, variable cytosol concentration,
Bsp input, simple linear regression); C: merged analysis (By and BQ are input, weighted nonlinear
Continued

Table 4-1. (Continued)
regression with one specific and one nonspecific component); D: merged analysis (similar to C,
but B is input to find one specific component only); E: merged free receptor plot
b p
(2-parameter simple linear regression performed with nonlinear regression program); F: merged
Hill plot (20%-80% occupancy only, fit by IMSL cubic spline subroutine); G: merged affinity
spectrum (a transform of the log (B-p/Bg) vs. -log F binding plot smoothed by cubic spline);
H: ratio of measured rate constants (described in chapter VI); I: individual Hill plots
(occupancy 0%-80%, simple linear regression).
b. "Asymptotic" s.e.m. generated by SAS nonlinear regression program (Ralston and Jennrich, 1978).
c. Determined from abscissa at 50% occupancy (i.e., logit [Bsp/Bg]=0).
d. Slope at 50% occupancy.
e. Includes 25 single ligand concentration ("saturation") assays.
f. Includes 9 single ligand concentration determinations.

Fig. 4-10. Scatchard plot (derived from the specific binding data of figure 4-7) depicting
the binding of [JH]dexamethasone to glucocorticoid receptors in perfused mouse
brain cytosol.
Experimental conditions are described in the legend to figure 4-7 and in Methods. The line
was fit by least-squares linear regression. Cytosol protein concentration was 6.6 mg/ml.
Equilibrium dissociation constant Kd = 1.2 nM, and receptor concentration BQ = 2.5 nM (380
fmole/mg cytosol protein). Inset: Hill plot (line fit by simple linear regression)
derived from the same specific binding data combined with the estimate of Bq generated by
the Scatchard plot. Regression includes points in the region where receptor occupancy (0 =
Bs /Bq) does not exceed .8 (or 80%). The slope of the line provides the estimated Hill
coefficient n = 1.03.

Bsp (nM)
4*
■P»

o
Fig. 4-11. Representative Scatchard plot depicting the binding of [ H]triamcino1one
acetonide (TA) to glucocorticoid receptors in perfused mouse brain cytosol.
Cytosol was prepared in buffer A, and pairs of samples (250 pi) were incubated for 48 h at
2°C with increasing concentrations of [ H]TA and, for one of each sample pair, a 200-fold
excess of unlabeled TA. 50 Ml aliquots were then assayed in triplicate by the DEAE filter
method for the determination of specifically bound steroid (B^). For the specific
experiment illustrated above the cytosol protein concentration was 5.5 mg/ml, and the total
3
[ H]TA concentration ranged from 0.32 to 17.6 nM. The line was fit by simple least-squares
regression. Equilibrium dissociation constant = 0.36 nM, and receptor concentration
Bq = 2.2 nM (410 fmole/mg cytosol protein). Inset: Hill plot derived from the same
specific binding data combined with the estimate of Bq generated by the Scatchard plot.
Hill coefficient n=1.00 (regression restricted to the region of occupancy 0 = B^/Bq not
exceeding .8 or 80%).

6-
4-
®sp
F
2-
—i
0.5
h r~
1.0 1.5
Bsp (nM)

Fig. 4-12. Scatchard plot (derived from the specific binding data of figure 4-8) depicting
the binding of [JH]corticosterone to the complete ensemble of saturable
corticosterone binding sites in perfused mouse brain cytosol.
Experimental conditions are described in the legend to figure 4-8 and in Methods. The line
was fit by simple least-squares linear regression. Cytosol protein concentration was
7.0 mg/ml. The data are deceptively consistent with a single, apparently homogeneous class
of high-affinity binding sites. Apparent equilibrium dissociation constant = 8.4 nM,
and total binding site concentration = 4.2 nM (600 fmole/mg cytosol protein). Inset:
Hill plot derived from the same specific binding data combined with the estimate of B^x
generated by the Scatchard plot. Hill coefficient n = 1.03 (restricted to the region of
occupancy 0 = Bsp/BMAX not exceeding .8 or 80%).

Bsp
~F~
0.5-
0.4
0.3
0.2-
0.1-
T
(nM)

3
Fig. 4-13. Representative Scatchard plot depicting the binding of [ H]corticosterione to
glucocorticoid receptors in perfused mouse brain cytosol.
Cytosol was prepared in buffer A, and pairs of samples (250 ul) were incubated for 16 h at
3
2°C with increasing concentrations of [ H]corticosterone and, for one of each sample pair,
a 200-fold excess of unlabeled dexamethasone. 50 yl aliquots were assayed in triplicate by
the DEAE filter method for the determination of specifically bound [ H]corticosterone that
can be displaced by dexamethasone. The cytosol protein concentration was 3.8 mg/ml, and
total [ H]corticosterone concentration range was 2.9-170 nM. The line was fit by simple
least-squares regression. Equilibrium dissociation constant = 8.6 nM, and receptor
concentration BQ = 1.8 nM (468 fmole/mg cytosol protein). Inset: Hill plot derived from
the same specific binding data combined with the estimate of Bq generated by the Scatchard
plot. Hill coefficient n = 0.97 (occupancy 0 = B^/Bq not exceeding .8 or 80%).

Bsp (nM)
cn
O

3
Fig. 4-14. Nonlinear regression analysis of the binding of [ H]dexamethasone to
glucocorticoid receptors in perfused mouse brain cytosol (derived from the
total binding data, BT, of figure 4-7 and displayed in the Scatchard coordinate
system).
Experimental conditions are indicated in the legend to figure 4-7, and the use of the
nonlinear regression program is described in Methods. The model to which the data were fit
consists of the sum of one saturable high-affinity (specific) component and one
nonsaturable (nonspecific) component as described by equation (4-6). The actual regression
3
equation does not contain F; it accepts By and (total [ Hjdexamethasone concentration)
as pairs of input variables and then regresses By on the relatively error-free variable Sy,
fitting the adjustable binding parameters K^, Bg, and C-j (the asymptotic "sink" of
nonspecific binding). Each input data point was weighted as 1/By^, consistent with the
assumption that the coefficient of variation or percentage error in the measurement of By
is constant over the range of By. For display the resulting complete 3-parameter
regression model was then plotted in the Scatchard coordinate system (curved line), and
each component was also plotted separately (2 straight lines). (Note that the x-axis is
plotted below y=0 in the figure.) Equilibrium dissociation constant K. = 1.1 nM, and
Q c. i
receptor concentration Bq = 2.4 nM (370 fmole/mg cytosol protein). = 2.4 x 10 M .
Agreement with the binding parameter estimates derived from the Scatchard plot of specific
binding fit by simple linear regression (figure 4-10) is excellent.

2.4-
Bj (nM)
cn
r\>

o
Fig. 4-15. Nonlinear regression analysis of the binding of [ H]corticosterone to the
complete ensemble of saturable corticosterone binding sites in perfused mouse
brain cytosol (derived from the total binding data, BT, of figure 4-8 and
displayed in the Scatchard coordinate system).
Experimental conditions are indicated in the legend to figure 4-8, and the use of the
nonlinear regression program is described in Methods. The model to which the data were fit
consists of the sum of one saturable high-affinity (specific) component and one
nonsaturable (nonspecific) component as described by equation (4-6). The actual regression
equation does not contain F; it accepts By and Sy (total [ Hjcorticosterone concentration)
as pairs of input variables and then regresses By on the relatively error-free variable Sy,
fitting the adjustable binding parameters K^, B^ (which replaces Bq in equation 4-6), and
C, (the asymptotic "sink" of nonspecific binding). Each input data point was weighted as
1 9
1/By , consistent with the assumption that the coefficient of variation or percentage error
in the measurement of By is constant over the range of By. For display the resulting
complete 3-parameter regression model was plotted in the Scatchard coordinate system
(curved line), and each component was also plotted separately (2 straight lines). (The
x-axis is plotted below y=0 in the figure.) Apparent equilibrium dissociation constant Kd
= 8.8 nM, and total binding site concentration B^ = 4.6 nM (656 fmole/mg cytosol
protein.) Cj = 0.73 x 10^ M~*. Agreement with the binding parameter estimates derived
from the Scatchard plot of specific binding fit by simple linear regression (figure 4-12)
is excellent.

^ H
Bt (nM)
cn

3
Fig. 4-16. Merged nonlinear regression analysis of the binding of [ H]dexamethasone to
glucocorticoid receptors in the perfused mouse brain cytosol (derived from the
values of total binding, BT, from 18 independent experiments) combined with the
individual estimates for eách experiment, of the receptor concentration (Bg)
derived from initial Scatchard plots such as that depicted in figure 4-10)V
The data and the resulting regression have been plotted in a "Scatchard-like" coordinate
system (where B$p or By has been replaced by By/Bg, the normalized value of total bound
steroid). Representative experimental conditions are indicated in the legend to
figure 4-7, and the use of the nonlinear regression program is described in Methods. The
model to which the data were fit consists of the sum of one saturable high-affinity
(specific) component and one nonsaturable (nonspecific) component as described by
equation (4-6). The actual merged regression equation does not contain F; it accepts BT,
3
Bg, and (total [ Hjdexamethasone concentration) as sets of input variables and then
regresses By on the variables and Bg, fitting the adjustable binding parameters Kd and
C, (the asymptotic "sink" of nonspecific binding). Each input data point was weighted as
1 2
1/By , consistent with the assumption that the coefficient of variation or percentage error
in the measurement of By is constant over the range of By. For display the resulting
complete 2-parameter regression model was plotted in the "Scatchard-like" coordinate system
(curved line), and each component was also plotted separately (2 straight lines). (Note
that the x-axis is plotted below y=0 in the figure.) Equilibrium dissociation constant
= 1.8 ± 0.1 nM (n = 18 experiments, 127 points). = 2.5 x 10^ M~*. Range of total
receptor concentration Bg: 2.1 - 3.9 nM; range of cytosol protein concentration 5.3 - 13.3
mg/ml.

Bt/B0F ( x I0"8 M’1 )
9SL

3
Fig. 4-17. Merged nonlinear regression analysis of the binding of [ H]corticosterone to
the complete ensemble of corticosterone binding sites in perfused mouse brain
cytosol (derived from the values of total binding, By, from 7 independent
experiments combined with the individual estimates, for each experiment, of the
receptor concentration, BM.Y, derived from initial Scatchard plots such as that
depicted in figure 4-12).
The data and the resulting regression have been plotted in a "Scatchard-1ike" coordinate
system (where Bgp or By has been replaced by By/B^, the normalized value of total bound
steroid). Representative experimental conditions are indicated in the legend to
figure 4-8, and the use of the nonlinear regression program is described in Methods. The
model to which the data were fit consists of the sum of one saturable high-affinity
(specific) component and one nonsaturable (nonspecific) component as described by
equation (4-6). The merged regression equation does not contain F; it accepts By, BMAX
(substituted for Bq), and (total [^H]corticosterone concentration) as sets of input
variables and then regresses By on the variables and B^x, fitting the adjustable
binding parameters Kd and Cj (the asymptotic "sink" of nonspecific binding). Each input
data point was weighted as 1/By^, consistent with the assumption that the coefficient of
variation or percentage error in the measurement of By is constant over the range of By.
For display the resulting complete 2-parameter regression model was plotted in the
"Scatchard-1ike" coordinate system (curved line), and each component was also plotted
separately (2 straight lines). (Note that the x-axis is plotted below y=0 in the figure.)
Equilibrium dissociation constant K. = 6.6 ± 0.3 nM (n = 7 experiments, 50 points).
Cl ^
Cj = 0.88 x 10 M . Range of total binding site concentration 4.1 - 7.5 nM; range
of cytosol protein concentration 4.8 - 9.3 mg/ml.

MAX
bT / BMAX
F ( xIO*8 M'1)
CD
H
s
00
PoPr-
Ó ^ oo ro cn
89 L

3
Fig. 4-18. Merged Hill plot analysis of the binding of [ H]dexamethasone to glucocorticoid
receptors in the perfused mouse brain cytosol (derived from 62 values of
specific binding, B , from 18 independent experiments combined with the
individual estimtes, for each experiment, of the receptor concentration (B )
derived from initial Scatchard plots such as that depicted in figure 4-10).
Only data points corresponding to a receptor occupancy (0 = BSp/BQ) between .2 (20%) and .8
(80%) were included in the analysis. The curve (almost linear) was fit by a cubic spline
algorithm that employs polynomials to smooth the data in accordance with a statistical
criterion; this method of regression contains no assumptions (other than the smoothness
criterion) concerning the basic form or shape of the curve, and thus is appropriate for
empirically determining both the shape of the Hill plot and the abscissa and slope at the
50% occupancy point (where logit 0=0). Representavie experimental conditions are
indicated in the legend to figure 4-7, and the use of the IMSL library cubic spline
subroutine is described in Methods. Equilibrium dissociation constant = 1.7 nM
(abscissa at logit 0 = 0); Hill coefficient (slope at logit 0 = 0) n = 0.99. Range of
total receptor concentration Bq:2.1 - 3.9 nM; range of cytosol protein concentration 5.3 -
13.3 mg/ml.

0.6-
L09'n
0.3-
0.0
9.4
Log F

o
Fig. 4-19. Merged Hill plot of the binding of [ H]corticosterone to the complete ensemble
of corticosterone binding sites in perfused mouse brain cytosol (derived from
28 values of specific binding, B , from 7 independent experiments combined
with the individual estimates, fSr each experiment, of the total binding site
concentration, BM.Y, derived from initial Scatchard plots such as that depicted
in figure 4-12).
Only points corresponding to binding site occupancy (e = BSp/B^) between .2 (20%) and .8
(80%) were included in the analysis. The curve (almost linear) was fit by a cubic spline
algorithm that employs polynomials to smooth data in accordance with a statistical
criterion; this method of regression contains no assumptions (other than the smoothness
criterion) concerning the basic form or shape of the curve, and thus is appropriate for
empirically determining the shape of the Hill plot and the abscissa and slope at 50%
occupancy (logit e = 0). Representative experimental conditions are indicated in the
legend to figure 4-8, and the use of the IMSL library cubic spline subroutine is described
in Methods. Equilibrium dissociation constant = 6.2 nM (abscissa at logit e = 0); Hill
coefficient (slope at logit 0 = 0) n = 0.95. Range of total binding site concentration
BMAX: 4,1 " nMl range of cytosol protein concentration 4.8 - 9.3 mg/ml.

h90
162
m
U_
-Log

3
Fig. 4-20. Merged "free receptor" plot of the binding of [ H]dexamethasone to
glucocorticoid receptors in perfused mouse brain cytosol (derived from the
values of specific binding, B , from 18 independent experiments combined with
the individual estimates, forseach experiment, of the receptor concentration
derived from initial Scatchard plots such as that depicted in figure 4-10). u
Representative experimental conditions are indicated in the legend to figure 4-7, and the
use of the nonlinear regression program to generate a standard error for the slope of the
line is described in Methods. The line was fit by unweighted, 2-parameter least-squares
linear regression and thus was not constrained by the regression equation to pass through
the origin. The ordinate is that of the normal Scatchard plot, but the abscissa has been
changed to the free receptor concentration (Bo_Bsp^ t0 a^ow the merging of experiments
having different total receptor concentrations. Equilibrium dissociation constant
(reciprocal of the slope) Kd = 1.5 ± 0.1 nM (n=18 experiments, 127 points). Range of total
receptor concentration BQ: 2.1 - 3.9 nM; range of cytosol protein concentration 5.3 - 13.3
mg/ml.

164
CL
CO
CO
(nM)

3
Fig. 4-21. Merged "free receptor" plot of the binding of [ H]corticosterone to the
complete ensemble of corticosterone binding sites in perfused mouse brain
cytosol (derived from the values of specific binding, B , from 7 independent
experiments combined with the individual estimates, forseach experiment, of the
total binding site concentration derived from initial Scatchard plots
such as that depicted in figure 4-TZ;.
Representative experimental conditions are indicated in the legend to figure 4-8, and the
use of the nonlinear regression program to generate a standard error for the slope of the
line is described in Methods. The line was fit by unweighted, least-squares linear
regression and was not constrained by the regression model to pass through the origin. The
ordinate is that of the normal Scatchard plot, but the abscissa has been changed to the
free receptor concentration (BMAX~^sp^ t0 a^ow the merging of experiments having different
total binding site concentrations and to display the resulting pattern of variance.
Equilibrium dissociation constant (reciprocal of the slope) = 7.0 ± 0.1 nM (n=7
experiments, 50 points). Range of total binding site concentration 4.1 - 7.5 nM,
range of cytosol protein concentration 4.8 - 9.3 mg/ml.

Bm - Bsp (nM) oj

3
Fig. 4-22. Affinity spectral analysis of the binding of [ H]dexamethasone to
glucocorticoid receptors in perfused mouse brain cytosol (derived from the
total binding data, By, of the experiment shown in figure 4-7).
Experimental conditions are described in the legend to figure 4-7, and the use of the
approximate method of finite differences is described in Methods. Affinity distribution A
is a transformation of binding data "predicted" by the complete 3-parameter nonlinear
regression displayed as the curved line in figure 4-14 (i.e., binding data that have been
"smoothed" by force-fit to a specific binding model); thus spectrum A is the representation
of a single homogenous class of high-affinity binding sites. Distribution B is a
transformation of total binding data that have been smoothed by the relatively
"assumption-free" cubic spline algorithm described in Methods. In both cases the
transformation was applied to binding functions expressed in the log By-log F coordinate
system. To generate spectrum A the curved regression line of figure 4-14 was transformed
to the log By-log F coordinate system before use of the finite differences method; spectrum
B was produced by smoothing the experimental By data in this same coordinate system with
the cubic spline algorithm before transformation to the affinity distribution. Both the
unconstrained spectrum and the comparison spectrum have been normalized by the total
receptor concentration (Bq) estimated by the regression displayed in figure 4-14. Spectrum
A (equivalent to the regression of figure 4-14): equilibrium dissociation constant = 1.1
nM; spectrum B (data smoothed by "model-free" cubic spline): equilibrium dissociation
constant = 1.1 nM. Method of finite differences: input spacing log K = 0.1, log a =
0.2. N(K) is dimensionless; the dimensionality of K is M“* (liters/mole). Inset: Total
binding (By) data of figure 4-7 smoothed by cubic spline algorithm in the log By-log F
coordinate system (By data points not shown). The subroutine uses a statistical criterion
to smooth the data, but there is no force-fit to any specific biophysical model as in the
regression of figure 4-14. The "spline-smoothed" binding curve was transformed into
spectrum B by the method of finite differences (Thakur et al., 1980).


3
Fig. 4-23. Affinity spectral analysis of the binding of [ H]corticosterone to the complete
ensemble of corticosterone binding sites is perfused mouse brain cytosol
(derived from the total binding data, BT, of the experiment shown in fig¬
ure 4-8).
Experimental conditions are described in the legend to figure 4-8, and the use of the
approximate method of finite differences is described in Methods. Distribution A is a
transformation of binding data "predicted" by the complete 3-parameter regression displayed
as the curve in figure 4-15 (i.e., binding data that have been "smoothed" by force-fit to a
specific binding model); thus, spectrum A is the representation of a single homogeneous
class of high-affinity binding sites. Distribution B is a transforamtion of total binding
data that have been smoothed by the relatively "assumption-free" cubic spline algorithm
described in Methods. In both cases the transformation method was applied to binding
functions expressed in the log By-log F coordinate system. To generate spectrum A the
curved regression line of figure 4-15 was transformed to the log By-log F coordinate system
before use of the finite differences method; spectrum B was produced by smoothing the By
data in this coordinate system with the cubic spline algorithm before transforamtion to the
affinity distribution. Both spectra have been normalized by the total binding site
concentration (B^) estimated by the regression displayed in figure 4-15. Spectrum A
(equivalent to the regression of figure 4-15): equilibrium dissociation constant = 8.8
nM; spectrum B (data smoothed by "model-free" cubic spline): equilibrium dissociation
constant K, = 5.3 nM. Method of finite differences: input spacing log K = 0.1, log
Q “I
a = 0.2. N(K) is dimensionless; dimensionality of K is M (liters/mole). Inset: Total
binding (By) data of figure 4-8 smoothed by cubic spline algorithm in the log By-log F
coordinate system (By data points not shown). The subroutine uses a statistical criterion
to smooth the data, but there is no force-fit to a specific model as in the regression
shown in figure 4-15. The "spline-smoothed" binding curve was transformed into spectrum B
by the method of finite differences (Thakur et al., 1980).

1.2-
—i 1 1 1 1 r
7.0 7.5 80 8.5 90 9.5
Log (K)

3
Fig. 4-24. Merged affinity spectral analysis of the binding of [ Hjdexamethasone to
glucocorticoid receptors in perfused mouse brain cytosol (derived from the
values of total binding, BT, from 18 independent experiments combined with the
individual estimates, for ¿ach experiment, of the receptor concentration, Bn,
derived from initial Scatchard plots such as figure 4-10).
Affinity distribution A is a transformation of normalized total binding data "predicted" by
the 2-parameter nonlinear regression displayed as the curve in figure 4-16 (i.e., binding
data that have been "smoothed" by force-fit to a specific binding model); thus, spectrum A
is the representation of a single homogeneous class of high-affinity binding sites.
Distribution B is a transformation of total binding data that have been smoothed by the
cubic spline algorithm described in Methods. In both cases the transformation was
performed on binding functions expressed in the log (Bj/Bq) - log F coordinate system.
Spectrum A was generated by transforming the regression curve of figure 4-16 to the log
(B-p/Bg) - log F coordinate system before application of the method of finite differences;
spectrum B was produced by smoothing the (B-^/Bq) data in this coordinate system with the
cubic spline algorithm before transformation to the affinity distribution. Spectrum A
(equivalent to the regression of figure 4-16): equilibrium dissociation constant Kd = 1.8
nM; spectrum B (data smoothed by "model-free" cubic spline): equilibrium dissociation
constant K, = 1.7 nM. Method of finite differences: input spacing log K = 0.1, log a =
a -1
0.2. N(K) is dimensionless; the dimensionality of K is M (liters/mole). Inset:
normalized total binding (B^/Bq) data smoothed by cubic spline algorithm in the log (B-jVBq)
- log F coordinate system (data points not shown). The subroutine uses a statistical
criterion to smooth the data, but the data are not constrained to fit any specific
biophysical model as in the regression of figure 4-16. The "spline-smoothed" binding curve
was transformed into spectrum B by the method of finite differences (Thakur et al., 1980).

00-
N ( K )
T 1 1 1 I ““ I
80 8.5 9.0 9.5 10.0 10.5
Log (K)
ro

Fig. 4-25. Merged affinity spectral analysis of the binding of [^Hjcorticosterone to the
complete ensemble of corticosterone binding sites in perfused mouse brain
cytosol (derived from the values of total binding, By, from 7 independent
experiments combined with the individual estimates, for each experiment, of the
total binding site concentration, B^, derived from initial Scatchard plots
such as figure 4-12).
Affinity distribution A is a transformation of normalized total binding data "predicted" by
the 2-parameter nonlinear regression displayed as the curve in figure 4-17 (i.e., binding
data that have been "smoothed" by force-fit to a specific binding model); thus, spectrum A
is the representation of a single homogeneous class of high-affinity binding sites.
Distribution B is a transformation of total binding data that have been smoothed by the
cubic spline algorithm described in Methods. In both cases the transformation was
performed on binding functions expressed in the log (By/B^) - log F coordinate system.
Spectrum A was generated by transforming the regression curve of figure 4-17 to the log
(By/B^) - log F coordinate system before application of the method of finite differences;
spectrum B was produced by smoothing the (By/B^x) data in this coordinate system with the
cubic spline algorithm before transformation to the affinity distribution. Spectrum A
(equivalent to the regression of figure 4-17): equilibrium dissociation constant Kd = 6.6
nM; spectrum B (data smoothed by "model-free" cubic spline): equilibrium dissociation
constant Kd = 4.6 nM. Method of finite differences:
input spacing log K = 0.1, log a =
,-1
0.2. N(K) is dimensionless; the dimensionality of K is M~ (liters/mole). Inset:
normalized total binding (By/BMAX) data smoothed by cubic spline algorithm in the log
(By/B^) - log F coordinate system (data points not shown). The subroutine uses a
statistical criterion to smooth the data, which are not constrained to fit a specific
biophysical model as in the regression of figure 4-17. The "spline-smoothed" binding curve
was transformed into spectrum B by the method of finite differences (Thakur et al., 1980).


175
3 3
[ Hjdexamethasone and [ H]TA to glucocorticoid receptors in perfused
mouse brain cytosol. Both plots are consistent with a single population
of non-cooperative, high-affinity glucocorticoid binding sites (for
which [ H]TA has higher affinity than [ Hjdexamethasone), and both
suggest similar estimates of the total receptor concentration (BQ).
Figure 4-12 (derived from the specific binding data of figure
4-8) is a conventional plot of the binding of [ Hjcorticosterone to the
complete ensemble of saturable corticosterone binding sites in perfused
brain cytosol; deceptively, it is also consistent with a single popu¬
lation of binding sites, but the resulting estimate of binding site
concentration (B^) is significantly greater than estimates obtained
with [ Hjdexamethasone and [ H]TA. Since it seemed likely that this
large ensemble of corticosterone binding sites contained a subset pool
of contaminating plasma transcortin (CBG) or intracellular CBG-like
binding sites that were distinct from the actual glucocorticoid
receptors, separate [ Hjcorticosterone isotherms were also generated by
incubating one of each pair of cytosol samples with a 200-fold excess of
unlabeled dexamethasone (instead of unlabeled corticosterone). With
this substitution the "nonspecific" correction (B^<-) increased
dramatically as expected (not shown), limiting the "specific" binding
3
BSp to the sites which bound both [ Hjcorticosterone and dexamethasone.
The plot of such an isotherm is shown in figure 4-13; it also is
consistent with a single class of non-cooperative binding sites (i.e.,
putative glucocorticoid receptors). (The apparent difference between
the estimates generated by figures 4-12 and 4-13 is not reproducible,
nor is the apparent difference between the Bg estimates generated by
figures 4-10 or 4-11 and figure 4-13; see summary table 4-1.) The

176
absence of evidence for a second class of lower affinity binding sites
(i.e., the lack of negative curvature or apparent negative
cooperativity) in experiments such as that of figure 4-12 thus suggested
that [ Hjcorticosterone had similar affinity for both the putative
glucocorticoid receptors and the non-receptor binding sites (i.e., the
[ Hjcorticosterone sites having very low affinity for dexamethasone).
The characteristics of the "nonglucocorticoid", CBG-like binding sites
were explored further, and will be discussed in chapter V.
In order to test the validity of binding parameter estimates
derived from conventional Scatchard plots fit by simple least-squares
linear regression, some isotherm data were analyzed by the weighted,
3-parameter nonlinear regression of total binding (By) on total
3
[ Hjsteroid concentration (Sy) as described in Methods. Figure 4-14
3
presents the results of such a reanalysis of the [ Hjdexamethasone
experiment already depicted in figure 4-7 and analyzed conventionally in
figure 4-10; and figure 4-15 depicts such a reanalysis of the
[ Hjcorticosterone binding data previously displayed in figure 4-8 and
analyzed in figure 4-12. The complete regressions and the separate
specific and nonspecific components of each were plotted in the usual
Scatchard coordinate system, and agreement of the resulting nonlinear
parameter estimates of Kd and Bq (or B^) with those derived from the
conventional Scatchard plots (figures 4-10 and 4-12) was excellent.
Several methods of combining the data from different individual
isotherms to generate a single "merged" estimate of were used to
analyze accumulated [ Hjdexamethasone and [ Hjcorticosterone binding
data from multiple experiments. Data sets were combined by the
weighted, 2-parameter merged nonlinear regression of total binding (By)

177
3
on total [ H]steroid concentration (SL) as described in Methods, with
insertion of the initial BQ (or B^) estimate for each experiment as an
input variable, instead of as a parameter to be estimated for the
complete ensemble of points. Figure 4-16 presents the results of such a
3
merged analysis of 18 independent [ Hjdexamethasone binding isotherms,
3
and figure 4-17 depicts such an analysis of 7 independent [ Hjcorti-
costerone isotherms. The complete regressions and the separate specific
and nonspecific components of each were plotted in the modified
Scatchard coordinate system as shown; the agreement of the resulting
nonlinear parameter estimates of with the means of the individual
estimates derived from conventional Scatchard plots was excellent (see
table 4-1).
Data sets were also combined in merged Hill plots (i.e., plots of
1°9 CBSp/(Bo“BSp)] or logit [e, fractional occupancy] vs. log F) that
were allowed to span the 20%-80% occupancy range. In such plots the
lines were fit by the polynomial cubic spline subroutine described in
Methods; this analysis provided both quantitative descriptions of the
shapes of the Hill plots at medium values of occupancy and merged
estimates of the dissociation constants (Kd). Figure 4-18 is such a
combined plot containing points from 18 independent [ Hjdexamethasone
binding isotherms, and figure 4-19 presents a Hill plot of points
derived from 7 independent [ Hjcorticosterone isotherms. The
"regression" lines in both figures 4-18 and 4-19 are nearly linear, and
both Hill coefficients (0.99 and 0.95, the instantaneous slopes of the
regression lines at the 50% occupancy level) were close to 1.0,
suggesting that the binding sites do not interact. Agreement of
estimates of Kd derived from these merged plots with the means of

178
conventional Scatchard-derived estimates was good (see table 4-1), and
the merged Hill coefficients confirmed the absence of cooperativity
suggested by Hill plots of individual experiments fit by linear
regression over a wide range of occupancy.
Data sets were also merged in simple unweighted "free receptor"
plots (fit by 2-parameter least-squares linear regression as described
in Methods, although only the slope estimates were of interest). Figure
4-20 is a combined "free receptor" plot containing points from the 18
independent [ H]dexamethasone isotherms, and figure 4-21 presents such a
reanalysis of the points derived from the 7 independent
3
[ Hjcorticosterone isotherms. Both regression lines passed near the
origin as expected, and the resulting estimates of Kd were in agreement
with the estimates generated by the other methods.
An attempt was made to analyze individual isotherm data sets by
transforming the total binding (B^) data to continuous affinity
distributions or spectra as described in Methods; the results were
disappointing for individual experiments containing relatively few data
points. Figure 4-22 presents such a spectral analysis of the
[ H]dexamethasone experiment depicted in figure 4-7 and analyzed also in
figures 4-10 and 4-14; and figure 4-23 depicts spectra derived from the
L Hjcorticosterone binding data previously displayed in figure 4-8 and
analyzed again in figures 4-12 and 4-15. In each figure the inset shows
the "smoothed" binding data that were transformed to the "unconstrained"
spectra (labeled "B"); the comparison spectra ("A") were transformed
from the 3-parameter nonlinear regression curves shown in figures 4-14
and 4-15 and are characteristic of a single class of noncooperative,
saturable binding sites. The shapes, widths, locations, and even the

179
numbers of peaks in the unconstrained ("B") spectra shown in figures
4-22 and 4-23 are not truly "representative". These characteristics
were quite variable within a series of independent replications,
reflecting the extreme sensitivity of the affinity distributions to
moderate levels of experimental error. For example, the suggestions of
apparent positive cooperativity (peak sharpening and high-affinity shift
with respect to the comparison spectrum) and the rather bizarre hints of
saturable low-affinity (nonspecific) binding displayed in figures 4-22
and 4-23 were not reproducible; other experiments that generated very
similar Scatchard plots yielded affinity spectra possessing very
different characteristics (e.g., broad, multimodal, low affinity-shifted
peaks suggestive of site heterogeneity or apparent negative
cooperativity). Individual isotherms simply did not contain enough data
points to permit useful application of the method, which is very
sensitive to the slight changes in the shape of the spline-smoothed
binding curves that are produced by different patterns of error
variance.
The affinity distribution analysis proved rather more useful when
it was applied to larger sets of data points formed by merging
independent isotherms (as described in Methods). Figure 4-24 is such a
spectral analysis of data from 18 independent [ H]dexamethasone binding
isotherms (127 points), and figure 4-25 presents the analysis of 50
points from 7 independent [ H]corticosterone isotherms. In each figure
the inset shows the "smoothed" normalized binding data (Bj/Bq) that were
transformed to the unconstrained spectra ("B"); the comparison spectra
("A") were transformed from the 2-parameter merged nonlinear regression
curves that are shown in figures 4-16 and 4-17 and that are each

180
indicative of a single saturable site. The unconstrained
3
[ H]corticosterone spectrum "B" (figure 4-25, derived from 50 points)
was still irregular and did not closely match the comparison spectrum
"A"; although the complete ensemble of [ Hjcorticosterone binding sites
contains at least two distinct subclasses (see Chapter V), the peculiar
shape and high-affinity shift of the peak were probably spurious, and we
do not consider them statistically significant. The high-affinity
region of the [ Hjdexamethasone spectrum "B", however, could be
superimposed upon its comparison spectrum "A" (figure 4-24). The large
input data set (127 points) and the sensitivity of the method to
subleties in the shape of the binding curve strengthened the conclusion
that the glucocorticoid receptors constituted a homogeneous class of
noninteracting sites, and the center of the "B" peak provided an
additional, independent estimate of the dissociation constant K^.
The measurements of equilibrium binding parameters for the three
3
[ H]1igands are summarized in table 4-1. The different methods of
3 3
analyzing the [ Hjdexamethasone and [ Hjcorticosterone isotherms
described above generated consistent estimates of for the binding of
[ Hjdexamethasone to putative glucocorticoid receptors (first column of
results) and (with the exception of the irregular [ Hjcorticosterone
merged affinity spectrum showing a high-affinity shift, method G) for
binding of [ Hjcorticosterone to the larger ensemble of all its binding
sites (last column). Because the data sets for the merged analyses were
derived from multiple independent experiments, the "asymptotic" standard
errors (indicated by the b superscript) are not sufficiently
conservative and should not be used as inferential statistics; they are
presented merely for comparisons among the different combined methods.

181
Reanalysis of the three experiments performed initially to measure the
efficiency of the DEAE filter assay (method B: incubation of a constant
3
concentration of [ Hjdexamethasone with samples of increasing cytosol
concentration) also generated a consistent estimate of for
3
[ Hjdexamethasone. Method D was merely a modification of the merged
nonlinear regression (method C) in which Bsp (instead of By) was an
input variable and the nonspecific term (containing the parameter C-j)
was neglected. As expected, the affinity of [ H]TA for the putative
receptors (second column) was significantly higher (at least 6-fold)
3
than that of [ H]dexamethasone. The significantly lower affinity of
3
[ Hjcorticosterone for the putative receptors (third column) was not
3
different from the combined affinity of [ Hjcorticosterone for the
complete ensemble of its binding sites (last column).
The ratios of measured rate constants (described in chapter VI)
also provided estimates of the dissociation constants for interactions
of the three ligands with the putative glucocorticoid receptors; these
estimates of were included in the table (method H) for comparison
with the equilibrium results. The equilibrium and kinetic estimates of
for [ Hjcorticosterone (third column) were in reasonable agreement.
In the case of each high-affinity synthetic ligand the measured
equilibrium dissociation constant was larger than the ratio of the
dissociation and association rate constants (k^/k.); this discrepancy
was 8-fold for [ H]TA and 4-fold for [ Hjdexamethasone. Although large,
these discrepancies were considerably smaller than those previously
reported to arise from studies of the binding of glucocorticoids to
cytosol preparations from other target tissues (e.g., Pratt et al.,
1975; Yeakley et al., 1980). The reduction or elimination of the

182
inactivation of unoccupied receptor sites in vitro achieved by the
inclusion of molybdate and other protective buffer ingredients has
probably contributed to the decrease in this discrepancy observed in
our experiments; the cause or causes of the residual disagreement are
unknown.
As expected, all Hill coefficients (methods I and F in table 4-1)
were not different from the value of 1.0 that suggests noninteracting
binding sites.
The measured functional binding site concentrations (Bq and Bf^x)
3
for the three [ Hjligands are also summarized in table 4-1. The
concentrations of putative glucocorticoid receptors measured with the
different ligands (first three columns) were in excellent agreement, and
these putative receptors comprised 63% of the complete ensemble of
3
[ H]corticosterone binding sites (column 4), which included a class of
3 3
CBG-like sites that lack affinity for [ Hjdexamethasone and [ H]TA (see
chapter V).
The total receptor concentration (Bq) was not consistently or
significantly affected either by the tissue: buffer ratio at
homogenization or by dilution of the cytosol with additional buffer
following homogenization. The left panel of figure 4-26 presents the
estimated receptor concentrations and the corresponding cytosol protein
concentrations for the independent [ Hjdexamethasone experiments. The
plot reveals the wide range of receptor concentrations estimated by the
different experiments; however, the slope of a regression line through
the points was not different from 0. (The slope of a regression line
through the points of a plot of estimated vs. cytosol protein
concentration for the different [ Hjdexamethasone isotherms was also

Fig. 4-26. Left panel: effect of cytosol protein concentration immediately following
homogenization (produced by varying the tissue:buffer A ratio) on the measured
total glucocorticoid receptor concentration (Bfi) in perfused mouse brain
cytosol. u
The results of 43 independent experiments are plotted in the figure. Measurements of
maximal specific binding were performed either by Scatchard analysis (n=18) or with single
ligand concentration (saturation with 2 x 10 M [ H]dexamethasone) assays (n=25).
Experimental conditions are described in the legend to figure 4-7 and in Methods. The
slope of a linear regression through these points is not different from 0. Right panel:
The effect of dilution with buffer A following homogenization on the total receptor
concentration (Bq) in perfused mouse brain cytosol. Three different pools of concentrated
cytosol were diluted as shown to 8 different concentrations and then divided into pairs of
samples. Following incubation for 12 h at 2°C with 2 x 10" M [ Hjdexamethasone and, for
one of each sample pair, a 200-fold excess of unlabeled dexamethasone, 50 yl aliquots were
assayed in triplicate by the DEAE filter assay for the determination of specific binding.
Total receptor concentration (Bq) was not significantly affected by dilution of the cytosol
following homogenization.

CYTOSOL PROTEIN (mg/ml)
00
-c*

185
not different from 0; not shown). Furthermore, the right panel of
figure 4-26 shows, for 3 independent pools of concentrated cytosol, that
dilution of initially concentrated cytosols with additional buffer did
not exert a significant effect on the subsequently measured
concentration of functional binding sites.
The two different methods used to calculate the equilibrium dis¬
sociation constants (K^.) for the binding of competing unlabeled ligands
to [ H]dexamethasone binding sites are illustrated in figure 4-27. The
figure presents a representative two-ligand competition "free-receptor"
plot used to determine K^. for the binding of unlabeled corticosterone
to putative receptors labeled with [ Hjdexamethasone in perfused brain
cytosol; the reciprocal of the slope provided an estimate of Kdi. The
points were derived (as described in Methods and in chapter III) from
the specific binding data of the two isotherms displayed in the
Scatchard plots in the left inset. These data were generated by the
"Edsall-Wyman" experimental design: the isotherm described by the
steeper line was generated without unlabeled corticosterone, and the
isotherm described by the plot having the reduced slope was generated in
a similar fashion with the same pool of cytosol, except that each pair
of tubes contained additionally the same concentration (8 nM) of
unlabeled corticosterone. The K.. was also calculated directly from the
slopes of these Scatchard plots (left inset, figure 4-27) by use of the
familiar Edsall-Wyman equation as described previously. Figure 4-28
shows a representative merged competition "free receptor" plot used to
determine the dissociation constant (K^.) for the binding of unlabeled
progesterone (P^) to putative receptors labeled with [ Hjdexamethasone.
The points were derived from 4 independent experiments that each

Fig. 4-27. Representative two-ligand competition "free receptor" plot used to determine the equilibrium
dissociation constant (Kg-) for the binding of unlabeled corticosterone (B) to glucocorticoid
receptors labeled with [aH]dexamethasone in perfused mouse brain cytosol.
The points were derived from the data displayed in the Scatchard coordinate system in the left inset. The
nomenclature of the figure conforms to that of chapter III, with the identification of L (labeled ligand)
with [ H]dexamethasone and C (competing ligand) with corticosterone (B). The plot is described in the
text and in detail in chapter III. The abscissa was calculated by equation (4-9); equation (4-9) was also
used, in conjunction with the known corticosterone concentration (Sq), to find the ordinate, which is the
bound/free ratio for the competing corticosterone. The line (equation 4-11) was fit by simple linear
regression and was not constrained to intersect the orgin. The reciprocal of its slope is the equilibrium
dissociation constant (K^. or K^) for corticosterone: K^. = 5.2 nM. Right inset: the abscissa of the
plot described above has been changed from total free receptor to total bound receptor concentration in
order to display the range of receptor occupancy (0) spanned by the experimental conditions; range of 9:
67% to 96%. Left inset: Representative experimental data (generated by the "Edsall-Wyman" experimental
design and displayed in the Scatchard coordinate system) used to determine the dissociation constant for
corticosterone () by competition with labeled [ Hjdexamethasone for glucocorticoid receptors. The
upper isotherm (-B,•) was generated as described in the text and in the legend to figure 4-7, and the
lower curve (+8 nM B,A) was generated in an identical fashion with the same pool of cytosol, except that
both members of each pair of tubes contained 8 nM unlabeled corticosterone to reduce the slope of the
"Scatchard" plot as depicted. The lines were fit by simple linear regression, and the [ Hjdexamethasone
dissociation constant and receptor concentration Bq were derived from the slope and intercept of the
upper [3H]dexamethasone Scatchard plot (#). These values of and Bq were used, in conjunction with the
reduced slope of the lower plot (A) 5 as input to equation (4-8) to calculate the K^. for corticosterone
(see text and also chapter III). The data (A were also transformed as described above into the
competition "free receptor" plot displayed in the figure. For the specific experiment displayed:
= 2.3 nM, Bq = 2.5 nM (270 fmole/mg protein); the protein concentration was 9.3 mg/ml, and the
corticosterone = 5.9 nM (by use of the Edsal1-Wyman equation).

0.2

Fig. 4-28. Merged competition "free receptor" plot used to determine the equilibrium
dissociation constant (K..) for the binding of unlabeled progesterone (P,)
glucocorticoid receptorsalabeled with [JH]dexamethasone in perfused mousé
brain cytosol.
to
The nomenclature of the figure conforms to that of chapter III, with the identification of
L (labeled ligand) with [ H]dexamethasone and C (competing ligand) with progesterone. The
points were derived from 4 independent experiments that employed the "Edsal1-Wyman"
experimental design. For each independent experiment a pair of isotherms was generated as
described in the text and in the legends to figures 4-7 and 4-27. One of the
[ H]dexamethasone isotherms was generated in the absence of competing progesterone; the
other isotherm was generated in the presence of a constant concentration of unlabeled
progesterone, which reduced the apparent affinity of the binding sites for the
[ H]dexamethasone. The [ Hjdexamethasone equilibrium dissociation constant and
receptor concentration Bq were derived from a Scatchard analysis of the isotherm generated
in the absence of progesterone. These values of and Bq were used, in conjunction with
the competition data from the tubes containing progesterone, to derive the points
displayed in the plot, which is described in the text and discussed in detail in
chapter III. The abscissa was calculated by equation (4-9); equation (4-9) was also used,
in conjunction with the known progesterone concentration (Sq), to find the ordinate, which
is the bound/free ratio for the competing progesterone. The line (described by equation
4-11) was fit by linear regression and was not constrained to intersect the origin. The
reciprocal of the slope is the equilibrium dissociation constant (K^. or K^) for
progesterone: K^. = 11.8 ± 1.0 nM (n=4). The progesterone concentrations for the
4 experiments were: 10, 10, 16 and 52 nM; the range of protein concentration:
5.3-10.0 mg/ml. Use of the nonlinear regression program to generate a standard error for
the slope of the line is described in Methods.

O.16-1
0.12-
0.08-
004-
0.4
0.8
Bo bl
B
C
00

190
employed the Edsall-Wyman experimental design. Since the free receptor
plot estimated only one binding parameter (Kdi), the points from the for
different experiments (which contained both different protein and
unlabeled progesterone concentrations) could be combined before the
regression (which was not constrained to pass through the origin) was
performed.
The results of the competition experiments are summarized in
table 4-2, which presents the estimates of the equilibrium dissociation
constants (K^) for the binding of selected steroids to the putative
receptors labeled by [ H]dexamethasone. The estimates of Kdi. were
calculated for each individual experiment both by the free receptor
method and by use of the Edsall-Wyman relation; the individual data sets
for each competitor were also combined by the merged free receptor
method. Additionally, the measured affinity of unlabeled dexamethasone
for the receptor subset of the complete ensemble of [ H]corticosterone
binding sites (described in Chapter V) was also included in the table
(first entry). Values of Kd- calculated by the Edsall-Wyman relation
were in excellent agreement with those derived from the free receptor
plots, and the merged estimates were not different from the means of the
individual determinations.
Based strictly upon their ability to stimulate the activity of
tyrosine aminotransferase (TAT) in hepatoma (HTC) cells, these steroids
(see table 4-2 for definitions of abbreviations) have been classified
(e.g., Rousseau and Schmit, 1977) as either optimal inducers (o: DEX, B,
F, ALDO), suboptimal inducers (s: DOC), or antiglucocorticoids
(a: P^, S, T); our experiments did not include steroids having truly
negligible affinity for the receptors (inactive steroids such as THB,

Table 4-2. Equilibrium dissociation constants (K^- values) for the binding of selected steroids to the
glucocorticoid receptors of perfused mouse brain cytosol. Tabulated values are calculated from the
same experimental data by three different methods as shown; see text and also chapter III for details.
The labeled ligand displaced by the competitors (with the indicated exception) is [ H]DEX. Values are
x ± s.e.m., with the number of determinations given in parentheses.
"FREE RECEPTOR" PLOTS: MEANS "EDSALL-WYMAN" EQUATION:
STEROID9 OF INDIVIDUAL EXPERIMENTS MERGED "FREE RECEPTOR" PLOT MEANS OF INDIVIDUAL EXPERIMENTS
(xl 0_9M)
(xl0”9
M)
(xl 0*
’9M)
DEX/[3H]Bb
1.0
± 0.2
(6)
1.0
±
0.1C
(6)
Not Applicable
B
4.7
± 0.6
(4)
4.7
±
0. 5C
(4)
5.3
+
0.6
(4)
DOC
8.5
± 2.5
(4)
8.9
±
1.5C
(4)
9.0
+
2.3
(4)
P4
12.6
± 1.9
(4)
11.8
±
1.0C
(4)
12.2
±
2.0
(4)
F
13.1
± 0.9
(4)
16.6
±
2.5C
(4)
13.4
±
1.1
(4)
ALDO
27.0
± 3.5
(4)
27.1
±
3.2C
(4)
27.0
±
3.3
(4)
S(DOF)
51.4
± 4.1
(3)
45.7
±
10.8C
(3)
42.1
±
2.0
(3)
T
591
± 62
(3)
616
±
110C
(3)
536
±
60
(3)
a. Definitions of abbreviations for trivial names of steroids: DEX = dexamethasone, B = corticosterone,
DOC = deoxycorticosterone, F = cortisol, ALDO = aldosterone, S(DOF) = cortexolone (deoxycortisol),
Continued

Table 4-2. (Continued)
T=testosterone.
3
b. Measured affinity of dexamethasone for the receptor subset of the total pool of [ H]corticosterone
binding sites. See text and chapter V.
c. "Asymptotic" s.e.m. generated by the nonlinear regression program (SAS).

193
tetrahydrocorticosterone). The ligands fell into the following order of
decreasing affinity (increasing Kdi) for the [ H]dexamethasone binding
sites: (DEX, o) > B (o) > DOC (s) > P4 (a) ^ F (o) > ALDO (o) > S (a) >
T (a), where the hepatoma TAT-inducer type (o, s, or a) has been
included in parentheses. The steroids of a given inducer category were
not clustered perfectly in the affinity rank order. Thus, the TAT
optimal inducer aldosterone had relatively low affinity, and the
antigluco- corticoid progesterone (P^) was as effective in competition
as the familiar glucocorticoid cortisol (F). The measured affinity of
progesterone (P^) for the mouse brain glucocorticoid receptors
(l hepatoma (HTC) cytosol [ Hjdexamethasone binding sites (Rousseau and
Schmit, 1977). Unlabeled dexamethasone had high affinity for the
receptor subset of the total pool of [ Hjcorticosterone binding sites
as expected.
Physiochemical Characteristics of Mouse Brain Glucocorticoid Receptors
The size and potential heterogeneity of the mouse brain cytosol
glucocorticoid receptor labelled with the nearly-irreversible agonist
[ H]TA were studied by gel filtration through Sephacryl S-300 in
buffer A containing additionally 150 mM KC1 as described in Methods.
Figure 4-29 presents a representative S-300 profile that displays the
in vitro stabilization by molybdate and other ingredients of buffer A
of a well-resolved and relatively large (77 A) [ H]TA-receptor complex.
Figure 4-30 illustrates calibration of the S-300 column. The sharpness
of the included peak and the moderate ionic strength afforded by 150 mM

Fig. 4-29. In vitro stabilization and molecular size of the mouse brain glucocorticoid
receptor during incubation and Sephacryl S-300 chromatography in buffer A
(containing additional 150 mM KC1).
Cytosol prepared in buffer A + 150 mM KC1 was incubated at 2°C for 12-16 h with 10 nM
[3H]TA (•) or 10 nM [3H]TA and a 200-fold excess of unlabeled TA (■). Following
3
incubation, free [ H]TA was removed by gel filtration in the same buffer on a large (1.5 x
98 cm) Sephadex G-25 (fine) column. Samples from the void volume of the 6-25 column (2
ml, approximately 5 mg/ml) were then chromatographed on a column of Sephacryl S-300
superfine (1.5 x 98 cm) at 12 ml/h in the same buffer (A + 150 mM KC1). Fractions (2 ml)
were collected, and 1 ml aliquots of these were assayed for radioactivity. Distribution
coefficients (K.) were calculated from elution volumes (V ), the void volume (V )
Q 6 j* O
indicated by blue dextran, and the total liquid volume (V.) marked by [ C]antipyrene,
[^Hjwater and [2-^H]deoxy(D)glucose: = (Vg - V0)/(V.j - VQ). The column was calibrated
with 7 standard proteins (chromatographed in separate runs as two different mixtures and
detected by absorbance at 280 nm), and the Stokes radius of the receptor complex (Rs) was
calculated from regressions of R$ vs several different functions of the standard protein
K. values as shown in figure 4-30. The different standard curves agreed closely; for the
U O
specific experiment shown R$ = 76 A. Mean and standard error from replicates are given in
table 4-3.

dpm/fraction ( xIO
V0 THYRO FERR ALDO BSA OVALB CHYMO
ro

Fig. 4-30. Calibration of the Sephacryl S-300 column with standard proteins of known
Stokes radius (Rs).
Samples (2 ml, in buffer A + .15 M KC1) of the standard proteins were run as the mixtures
"A" or "B" described below. Column conditions are described in the legend to figure 4-29.
o o
Mixture "A": blue dextran, void volume (VQ); ferritin, 61 A; aldolase, 48.1 A; ovalbumin,
30.5 A; RNAase, 16.4 A; [3H]2-deoxy(D)glucose, total liquid volume (V.). Mixture "B":
O O 1 o
thyroglobulin, 85 A; bovine serum albumin, 35.5 A; chymotrypsinogen A, 20.9 A;
[14C]antipyrene or [3H]water, total liquid volume (V^). Fractions were assayed by
absorbance at 280 nm. Distribution coefficients were calculated as described in the
text and in the legend to figure 4-29. Standard curves were generated by the linear
methods of Porath (1963) and Ackers (1967), and by the nonlinear regression of Laurent and
Ki1 lander (1964). The three methods of regression are in close agreement. In the method
of Ackers (1967) the ordinate y is defined by the relation = 1 - erf(y), where erf(y)
is the standard error function derived from the normal distribution. In the method of
Laurent and Killander (1964) the data are fit by the equation Kd = exp[- Cj(Rs + C2) ],
where C, and C0 are the adjustable parameters of the regression. This method also may be
i ¿ i/2
linearized (not shown) by plotting the Stokes radius R$ vs (-In K^) for the standard
proteins.

0.8n
20 30 40 50 60 0 70 80 90
STOKES RADIUS (A)

198
KC1 in the buffer suggested that although it could possibly be for
oligomeric, the large hormone-receptor complex was not merely an
artifactual aggregate formed by homogenization in hypotonic medium. The
peak was not, however, completely symmetrical; it had a small shoulder
O
at about 65 A that accounted for approximately 15% of the total area.
The presence of 150 mM KC1 was not required for the resolution of the
major peak, nor was the peak signficantly shifted or altered by the
addition of 350 mM KC1 to the basic buffer A (not shown). In the
absence of molybdate the S-300 profile was influenced by the ionic
strength and was not completely reproducible, frequently revealing minor
peaks having smaller Stokes radii (not shown). The exact locations and
the precise conditions leading to the probable proteolytic formation of
these secondary peaks were not studied further, but they may be related
to proteolytic fragments of glucocorticoid receptors observed previously
that retained functional steroid binding sites (e.g., Sherman,
Pickering, Rollwagen and Miller, 1978; Wrange and Gustafsson, 1978).
Although the complete profile was not reproducible in the absence of
o
molybdate, the major peak was resolved well at 59 ± 1 A (n=8) in buffer
containing 150 mM KC1, and the slight shoulder observed with molybdate
(e.g., figure 4-29) was absent; this result is consistent with previous
o
measurements (performed without molybdate) of 57-61 A for the radii of
[ H]TA- and [ Hjdexamethasone- receptor complexes extracted from rat,
mouse and human tissues (e.g., Stevens and Stevens, 1979; Wrange,
Carlstedt-Duke and Gustafsson, 1979). In hypotonic buffer (without
o
molybdate) the 59 A peak was shifted forward toward the position of the
large species observed in the presence of molybdate. The relation of
the large complex observed in the presence of molybdate to the smaller

199
one found in its absence is not known, but it is possible that
signficant activation (transformation) occurred at moderate ionic
strength in the absence of molybdate (e.g., Milgrom, Atger and Baulieu,
1973). Thus, the different Stokes radii may be a consequence of activa¬
tion; this possibility requires further investigation by measurement of
the Stokes radius of the activated receptors in the presence of
molybdate.
Following S-300 chromatography the sedimentation behavior of the
partially purified [ H]TA-receptor complex was investigated by
centrifugation of the pooled, concentrated S-300 column fractions
containing the receptor peak through glycerol gradients (made up in
buffer A containing 150 mM KC1) as described in Methods. Although the
resulting sedimentation patterns were not completely reproducible,
figure 4-31 presents a representative profile that displays the two
wel1-resolved peaks that were typical of this experiment. The positions
of the two peaks (A = 9.7 ± 0.4 S and B = 3.7 ± 0.1 S) were reasonably
reproducible, but the ratio of the peak areas was quite variable.
Furthermore, in some experiments one or the other of the two peaks was
completely absent. Sedimentation of crude cytosol samples labelled with
[ H]TA (not partially purified by S-300) revealed two peaks at
approximately the same locations, but they were not as well resolved as
those described above; the crude cytosol profiles were heterodisperse,
and some labelled material was found throughout the 3-12 S range (not
shown). Attempts to measure the Stokes radius (by S-300 chromatography)
of [ H]TA-receptor complexes partially purified first by gradient sedi¬
mentation were disappointing; little bound radioactivity was recovered
from the S-300 column. In summary, prolonged rate sedimentation of the

Fig. 4-31. Sedimentation of mouse brain glucocorticoid receptors in buffer A (containing
additional 150 mM KC1) after partial purification by Sephacryl S-300
chromatography.
Following S-300 chromatography of cytosol labeled with [$H]TA (•) or [$H]TA and a 200-fold
excess of unlabeled TA (â– ) (described in figure 4-29) aliquots (1 ml) from each of the 5
high fractions bracketing the peak of the S-300 profile (e.g., fractions 37-41 in figure
4-19) were pooled and concentrated 10-fold by ultrafiltration (Amicon Minicon B-15) to a
volume of 500 yl. Aliquots (250 yl) of the concentrated, pooled S-300 fractions were then
centrifuged at 2°C for 20 h at 234,000 g (average) through 5 ml gradients of 12.5 - 25%
(w/v) glycerol in the same buffer (A + .15 M KC1). The cellulose nitrate tubes were
punctured, and 175 yl fractions were collected and assayed for radioactivity. The value
of S2q for the indicated peaks A and B was calculated from the linear regression of
$20 w vs ^mentation distance (Martin and Ames, 1961) for the standard proteins, which
were run on parallel gradients as 250 yl samples in the same buffer (A + .15 M KC1):
ovalbumin, 3.6 S; BSA, 4.3 S; IgG, 7.4 S. Standard proteins were labeled to low specific
activity ([^CH^l-methylated) by the method of Rice and Means (1971). For the specific
experiment depicted, the sedimentation coefficients were: peak A, 9.2 S; peak B, 3.3 S.
Means and standard errors from replicates are presented in table 4-3.

OVALB BSA IgG
TOP
FRACTION NUMBER
PO
o

202
partially-purified 77 A [ HjTA-receptor complex in buffer A supplemented
with 150 mM KC1 revealed two components that sedimented at 9.7 ± 0.4 S
and 3.7 ± 0.1 S; the ratio of the peak areas was not reproducible.
The mean value of the receptor Stokes radius measured by S-300
chromatography and the mean sedimentation coefficients of the two peaks
observed in the glycerol gradient profile are listed in table 4-3. Each
sedimentation coefficient was combined with the single value of the
Stokes radius and also with the assumed values of the partial specific
volume and degree of hydration, in order to estimate the molecular
weights, frictional ratios, and axial ratios that would result if either
of the sedimentation peaks also possessed the measured Stokes radius.
Apparently the molecular species resolved in the 9.7 S peak (A)
O
corresponded to the 77 A receptor complex; the degree of asymmetry
estimated by assuming corespondence for the slower-sedimenting peak (B)
was highly improbable. Thus, the molybdate-stabilized [ H]TA-receptor
complex has an apparent molecular weight of 315,000 daltons and is
moderately asymmetric. The extent of receptor hydration (6) is unknown;
the value 6 = 0.2 g H^O/g protein was arbitrarily assumed in order to
facilitate a direct comparison with the sizes and shapes reported by
Sherman and her colleagues (e.g., Niu et al., 1981) for molybdate-
stabilized steroid receptors. In hypotonic buffer containing 20 mM
Na^MoO^, estrogen, progestin and glucocorticoid receptors from a variety
of tissues all shared hydrodynamic parameters, molecular weights and
shapes nearly identical to those listed in table 4-3 for the
rapidly-sedimenting peak (A); Vedeckis (1981) also reported the value of
o
77 A for the radius of glucocorticoid receptors from a mouse pituitary
3
tumor cell line. These large, molybdate-stabilized [ H]TA-receptor

203
Table 4-3. Physical properties of the molybdate-stabilized mouse
brain glucocorticoid receptors labeled with [ H]TA. Values listed
are, where appropriate, x ± s.e.m. The number of experiments is shown
in parentheses. See figures 4-29 and 4-31 and "Methods" for details.
A and B refer to the faster and slower-sedimenting peaks observed in
the centrifugation experiments. The tabulated calculations arbi¬
trarily assume that peaks A and B both correspond to the same value
of R$ (see text for discussion).
Parameter
Gradient Peak A
Gradient Peak
R<. (xl0"^cm)
77 ± 2 (10)
77 ± 2 (10)
S20,w
9.7 ± 0.4 (4)
3.7 ± 0.1 (7)
M (daltons)
315,000 ± 20,000
120,000 ± 5000
f/fo (6=0)
1.70
2.34
f/fo (6=0.2 g/g)
1.57
2.16
b/a (6=0)
13:1 (prolate)
29:1 (prolate)
b/a (6=0.2 g/g)
10:1 (prolate)
24:1 (prolate)

204
complexes may be oligomeric, since the molecular weights of purified for
receptor polypeptides are much smaller than 315,000 daltons (e.g.,
Govindan and Sekeris, 1978; Wrange, Carlstedt-Duke and Gustafsson, 1979;
Nordeen, Lan, Showers and Baxter, 1981).
Four of the five immobilized-dye columns included in the Amicon
Dyematrex kit retained large fractions of the total pool of
3
[ Hjdexamethasone receptor complexes when dye-ligand screening was
performed as described in Methods (data not shown). Red HE3B adsorbed
the entire pool of receptors. Blue F3GA retained approximately 80%, and
the Green A and Blue B columns bound about half the receptor pool. None
of the potential "biospecific" affinity eluents released a significant
amount of [ Hjdexamethasone from any column. Binding to the dyes was
very tight; the high salt and urea steps were required for the release
3
of [ Hjdexamethasone, which was complete only after the final treatment
with 8 M urea and 0.5 M NaOH. The nature of the dye-receptor
interaction is unknown, but hydrophobic interactions are believed to
dominate the behavior of many proteins during dye chromatography (Dean
and Watson, 1979). The results suggested that the receptors may possess
surface hydrophic domains other than the steroid binding sites
themselves, and that hydrophic interaction chromatography might prove
helpful in a receptor purification scheme. The failure of some of the
dye columns to adsorb the entire pool of steroid-receptor complexes
requires further investigation and should not be considered strong
evidence for receptor heterogeneity.

205
Discussion
We have found that perfused mouse brain cytosol contains a single,
apparently homogeneous class of saturable, high-affinity binding sites
for the synthetic glucocorticoid agonists [ Hjdexamethasone and [ HjTA;
these binding sites possess the steroid specificity and other
generally-accepted characteristics of putative glucocorticoid receptors.
The mouse brain is probably fundamentally similar to the rat brain in
possessing additionally a low concentration of specific mineralocorti-
coid receptors that eventually become saturated in vitro at very high
[ H]dexamethasone concentrations; this inference is derived from
3
observations of saturable high-affinity rat brain [ H]aldosterone
3
binding sites from which [ H]aldosterone is displaced by high concentra¬
tions of dexamethasone (Anderson and Fanestil, 1976; Moguilewsky and
Raynaud, 1980; Veldhuis, van Koppen, van Ittersum and de Kloet, 1982).
However, these rat brain mineralocorticoid binding sites have never been
revealed by Scatchard analysis as a second class of lower-affinity,
saturable [ H]dexamethasone binding sites, nor have the experiments
reported here disclosed a second class of saturable mouse brain
3
[ Hjdexamethasone binding sites. Furthermore, the concentration of
3
putative glucocorticoid binding sites measured with [ H]TA (which
possesses very low mineralocorticoid activity) was not less than the
estimate obtained with [ Hjdexamethasone. Thus, we do not believe that
mineralocorticoid sites have been inadvertently confounded with gluco¬
corticoid receptors in any of the experiments reported here.
Perfused mouse brain cytosol also contains a class of corticos¬
terone binding sites that lack affinity for the synthetic
glucocorticoids dexamethasone and TA; these sites have many of the

206
properties of transcortin (CBG). Although it has not been established
that these binding sites are intracellular in vivo, their concentration
in plasma may not be sufficient to explain their presence in perfused
brain cytosol as a contaminant derived from residual blood remaining in
the brain after perfusion (see Chapter V). These sites have not,
however, been observed in perfused rat hippocampal cytosol (e.g.,
Wrange, 1979; Veldhuis et al., 1982).
Subcellular fractionation in the hypertonic medium (buffer A)
revealed negligible concentrations of high-affinity [ Hjdexamethasone
binding sites in nuclear, mitochondrial, and microsomal fractions.
This finding does not preclude the existence of membrane-associated
glucocorticoid binding sites differing from the soluble sites in steroid
affinity and specificity. Rat brain synaptic plasma membranes have been
reported to contain saturable (but very low affinity) sites that bind
corticosterone, dexamethasone and TA (Towle and Sze, 1978). Other,
CBG-like plasma membrane-associated glucocorticoid binding sites lacking
affinity for dexamethasone and TA have also been reported (e.g., Koch,
Lutz-Bucher, Briaud and Mialhe, 1978; Harrison, Balasubramanian,
Yeakley, Fant, Svec and Fairfield, 1979; Harrison, Yeakley and Fant,
1980). Such "unusual" binding sites would not have been detected in our
experiments that employed only a single, moderate concentration (2 x
10 M) of [ H]dexamethasone to assay the concentration of specific
binding sites in each subcellular fraction; the possibility that mouse
brain contains membrane-associated binding sites will require further
investigation. Furthermore, the in vivo subcellular localization of the
soluble binding sites is unknown. Subcellular redistribution of the
unoccupied glucocorticoid binding sites may have occurred as a function

207
of the aqueous homogenization procedure, and future studies with non-
aqueous nuclear isolation methods (e.g., Martin and Sheridan, 1980) may
reveal significant nuclear concentrations of unoccupied soluble
glucocorticoid binding sites.
The DEAE filter assay was convenient, reproducible and linear; it
was used whenever the binding sites could be confined to the small
volumes that can be absorbed by individual filter disks. It has been
suggested that heat-activated hepatoma (HTC) cell glucocorticoid
receptors may not bind to the Whatman DE-81 filter disks with high
efficiency (Baxter, Santi and Rousseau, 1975); we have found very
recently that this is also the case with activated mouse brain gluco¬
corticoid receptors (Luttge and Gray, unpublished). This failure to
bind strongly to DE-81 filters stands in contrast to the efficient
binding of activated glucocorticoid receptors to DEAE-cellulose and DEAE
Sephadex A-50 (e.g., Vedeckis, 1981; Parchman and Litwack, 1977). The
two methods used to estimate the efficiency of the DEAE filter assay for
the measurement of unactivated, molybdate-stabilized glucocorticoid
receptors generated relatively high and equivalent estimates (76% ± 2%).
Furthermore, the data presented in figure 4-4 suggest that the con¬
ductivity of buffer A is not dangerously close to the threshold value
required for the elution from the DEAE filters of the molybdate-
stabilized unactivated receptors that we have studied. Finally, we have
noticed that much of the nonspecific binding observed with the filter
assay is the result of direct adsorption of steroid by the filters, and
thus is not related to the presence of the biological sample.
The requirement that a sulfhydryl-protective agent is necessary to
preserve functional unoccupied glucocorticoid binding sites in mouse

208
brain cytosol is consistent with its requirement for the preservation of
binding sites in cytosol prepared from thymocytes, lung, and spleen
(Sando, Hammond, Stratford and Pratt, 1979; Granberg and Ballard, 1977),
but contrasts strongly with the absence of such a DTT requirement in
cytosol prepared from other tissues such as liver, kidney, heart,
lymphocytes and fibroblasts (Granberg and Ballard, 1977; Wheeler, Leach,
LaForest, O'Toole, Wagner and Pratt, 1981; Sando, LaForest and Pratt,
1979). This highly variable requirement for DTT may be a consequence of
very different tissue concentrations of endogenous sulfhydryl protective
compounds that contribute to the preservation of functional glucocorti¬
coid binding site conformations in vivo by maintaining a favorable
intracellular redox state (e.g., Granberg and Ballard, 1977).
The role of molybdate in the in vitro stabilization of unoccupied
and also of nonactivated glucocorticoid receptor sites is considerably
more mysterious than that of DTT in the preservation of functional
unoccupied binding sites. Some molybdate effects may also be tissue
dependent; for example, the ability of molybdate to convert activated
heart cytosol glucocorticoid receptors back to the nonactivated form
(Seleznev, Shnyra, Volkova, Smirnov, Djozdjevic-Markovic, Lan and
Baxter, 1981) contrasts with its reported failure to reverse the
activation of liver cytosol glucocorticoid receptors (Barnett et al.,
1980) and with our very recent observation that it fails to reverse the
activation of mouse brain glucocorticoid receptors (Luttge and Gray,
unpublished). In any case, the importance of molybdate in the
prevention of decapacitation cannot be overestimated. The
decapacitation rate observed at 2°C in the absence of molybdate
(figure 4-5) is high enough to prevent the accurate estimation of ligand

209
affinity from an isotherm generated by the prolonged (e.g., 16 h)
incubation of cytosol samples, some of which contain low, subsaturating
steroid concentrations; decapacitation of unoccupied receptors in the
samples incubated with low concentrations of [ Hjsteroid would lead to a
serious overestimate of the dissociation constant (Kd). Thus, isotherms
generated without molybdate may be distorted either by a failure to at¬
tain equilibrium (as a result of inadequate incubation time) in the
samples containing low ligand concentrations or by the decapacitation of
unoccupied binding sites at the low ligand concentrations; the results
of such experiments (e.g., Veldhuis et al., 1982; Meyer and McEwen,
1982) must therefore be questioned.
In addition to protecting unoccupied binding sites, molybdate also
facilitates the gradual conversion of some latent or "cryptic" binding
sites to the functional steroid-binding form. Figure 4-5 reveals a
signficant increase in brain cytosol binding sites as a function of
cytosol "aging" (without steroid) in the presence of molybdate at 2°C,
12°C, and 22°C; this increase is consistent with the gradual
molybdate-dependent conversion of latent to functional binding sites
observed with thymocyte, lymphocyte, and liver cytosol preparations
(Sando et al., 1979; Wheeler et al., 1981; Barnett et al., 1980). Many
aspects of the in vitro up and down-regulation of glucocorticoid
receptors are currently under investigation; at present none are well-
characterized or understood. As examples, we have observed (in the
absence of molybdate) that calcium ion promotes the decapacitation of
functional glucocorticoid binding sites, that higher cytosol protein
concentrations decrease the rate of decapacitation, and that components
of a particulate subcellular fraction mediate an ATP-dependent reduction

210
in the rate of loss of binding sites (Luttge, Densmore and Gray,
unpublished; Luttge et al., 1982).
The different methods of analyzing the equilibrium isotherm data
3
produced, for a given [ H]steroid, estimates of that were in agree¬
ment (table 4-1); none of the merged methods generated an estimate of
the [ H]dexamethasone affinity that was different from the mean of the
estimates derived from individual Scatchard plots (method A). None of
the merged methods (i.e., C,D,E,F,G) was used to estimate BQ (the total
binding site concentration); the values of Bq derived from initial
Scatchard plots were input as variables so that Bq could be eliminated
from the set of adjustable regression parameters. The mean of the
estimates derived from individual Scatchard plots (method A) and its
relatively conservative standard error were chosen as the "best"
estimate of for comparison with reports from other laboratories.
The methods (C and G) that included "nonspecific" binding in the
regression model (i.e., that predicted total binding, B^.) generated
estimates of that were equivalent to those produced by the
regressions (i.e., A,B,D,E,F) that predicted specific binding (B$p).
When derived from a large input data set, the merged affinity spectrum
(method G) provided a sensitive test for apparent site cooperativity
or heterogeneity.
Previous studies (e.g., Pratt et al., 1975; Yeakley et al., 1980)
of glucocorticoid binding kinetics have consistently shown a lack of
agreement between equilibrium and kinetic estimates of K^; typically,
the discrepancies have been highly correlated with the affinity of the
ligand and are largest for the synthetic high-affinity agonists (TA
and dexamethasone), but even the physiological steroid

211
3
[ H]corticosterone usually has produced a significant (several-fold)
discrepancy. For example, discrepancies of 79-fold, 12-fold, and
7-fold were reported for measurements with [ H]TA, [ Hjdexamethasone,
O
and [ Hjcorticosterone, respectively, in pituitary tumor (AtT-20)
cell cytosol (Yeakley et al., 1980). The discrepancies that we have
observed are considerably smaller, but they remain significant for
TA and dexamethasone. We cannot easily explain these discrepancies as
artifacts resulting from the failure to reach equilibrium in the TA and
dexamethasone isotherm experiments, since no increase in binding in the
tubes containing low ligand concentrations was observed when incubations
were extended beyond the reported times. Furthermore, in the standard
buffer A the unoccupied sites were inactivated at a negligible rate;
so that it is unlikely that an apparent equilibrium was merely a tempor¬
ary steady state resulting from the combination of increasing receptor
occupancy and a concomitant loss of unoccupied sites. Agreement of the
equilibrium and kinetic estimates of for the lower-affinity ligand
corticosterone was reassuring, but an explanation for the residual dis¬
crepancies for dexamethasone and TA remains elusive.
We have not made a systematic effort to study the total glucocorti¬
coid binding site concentration (Bq) as a function of the cytosol
protein concentration; nor have we investigated, by systematically
measuring Bq as a function of the time after adrenalectomy, the
possibility that adrenalectomy stimulates a gradual up-regulation of
functional binding sites (e.g., Stevens et al., 1975). Although the
slope of a regression line (not shown) fit to the plot (figure 4-26)
of Bq vs cytosol protein concentration was not different from 0, the
range and standard deviation of Bq were large. The source of this

212
variability is not obvious, since the pooling of brains to produce the
cytosol for a specific experiment should have reduced the effect of
animal individual differences on the standard deviation of the inde¬
pendent estimates of Bg. Although the result was not surprising, the
absence of a correlation between Bg and cytosol protein concentration
has not been a universal finding; dilution experiments with cytosol
derived from other tissue sources have sometimes revealed a strong
effect of cytosol protein on the concentration of functional sites
(sometimes attributed to the presence of an endogenous modulator of the
steroid binding sites; e.g., Katsumata, Baker and Goldman, 1981).
The measured specificity of the [ H]dexamethasone binding sites
(table 4-2) was consistent with that expected of putative glucocorticoid
receptors. The specificity of the mouse brain receptors may be compared
with the following sequences of decreasing steroid affinity (increasing
Kj.¡) for [ Hjdexamethasone or [ H]TA binding sites in hepatoma (HTC)
cell cytosol, rat hippocampal cytosol, and chick thymus cytosol:
(DEX) > B > DOC ^ F > ALDO > > S > T, hepatoma cells (Rousseau and
Schmit, 1977); DOC ^ B > P^ ^ DEX > ALDO, rat hippocampus (Veldhuis et
al., 1982); and (DEX) > DOC ^ P4 > B ^ F > ALDO > S > T, chick thymus
(Aranyi, 1982, measured by a kinetic method developed recently). The
affinity sequence F > ALDO > S > T has been found consistently by all
investigators; the relative affinities of B, DOC, and F, however, have
not always been in agreement. Consistent with the aforementioned
measurements of steroid affinity for glucocorticoid receptors in chick
thymus cytosol (Aranyi, 1982) and rat hippcampal cytosol (Veldhuis et
al., 1982), we have found that progesterone has high affinity for the
putative mouse brain receptors; progesterone possessed a significantly

213
lower affinity for the hepatoma (HTC) cytosol glucocorticoid receptors
(Rousseau and Schmit, 1977). Although it is difficult to predict
intracellular steroid concentrations from measured plasma concentra¬
tions, and although in vivo (37°C) steroid affinities have not been
measured, the observed in vitro affinity of P^ for the mouse brain
glucocorticoid receptor sites is probably high enough to assure their
saturation by the extremely high levels of the circulating antigluco¬
corticoid (360 nM) found in the pregnant mouse (Murr, Stabelfeldt,
Bradford and Geschwind, 1974). The possible physiological consequences
of a lengthy blockade of receptor-mediated glucocorticoid mechanisms
during pregnancy are unknown. The observation that corticosterone has
higher affinity for the rat hippocampal [ Hjdexamethasone binding sites
than unlabeled dexamethasone itself (Veldhuis et al., 1982) is without
precedent in the glucocorticoid literature and stands in contrast to our
finding that unlabeled dexamethasone possesses high affinity for the
putative receptor subset of the ensemble of whole mouse brain
3
[ Hjcorticosterone binding sites (table 4-2).
The competitor dissociation constants (Kdi values) calculated by
the "free receptor" method were in agreement with those calculated with
the Edsall-Wyman relation describing the effect of a constant
concentration of a competitive inhibitor; as expected, the Kdi values
for the higher affinity competitors B and DOC calculated by the free
receptor method were slightly lower (indicating higher affinity) than
those calculated with the Edsall-Wyman equation, but these differences
were not significant. The values of Kdi- for the binding of unlabeled
dexamethasone to the receptor subset of the [ H]corticosterone binding
sites and for the binding of unlabeled corticosterone to the

214
3
[ H]dexamethasone binding sites were smaller (indicating higher
affinity) than the values estimated directly with, respectively,
[ H]dexamethasone and [ Hjcorticosterone. These discrepancies may have
resulted from the possible failure of the complex two-ligand mixtures to
attain complete equilibrium. It is relevant that a continuous increase
with time in steroid values for mammary gland glucocorticoid binding
sites labeled with [ H]dexamethasone (measured by the competitive
displacement "ED^g" method at 0°C) was observed when incubations were
prolonged up to 44 h, well beyond the time required for the attainment
of equilibrium in the absence of the unlabeled inhibitors (Weisz,
Hutchens and Markland, 1982). The times required for such two-ligand
mixtures to approach equilibrium depend on the steroid kinetic
parameters and cannot be estimated easily, even if all kinetic
parameters are known; such a simulation would require the numerical
integration of the two simultaneous binding rate equations (see
chapter II). Thus, some steroid competition experiments may
require extremely long incubations; in the future it will be necessary
to verify empirically that a steady state has been attained for each
ligand concentration in such an experiment. Most published steroid K^.
measurements may thus be underestimates of the "true" equilibrium
values.
It is interesting that the size and shape of the large,
non-activated, molybdate-stabilized mouse brain [ H]TA-receptor complex
(table 4-3, peak "A") are identical to those of molybdate-stabilized
estrogen, progestin and glucocorticoid receptors from a variety of
tissue sources (e.g., Hutchens, Markland and Hawkins, 1981; Niu et al.,
1981; Vedeckis, 1981). A single recent observation has indicated that

215
the large 9S receptor forms may actually exist in vivo and are not
merely molybdate-generated artifacts: very rapid ( % 2 ti) sucrose
gradient sedimentation of cytosol progesterone receptors in a vertical
rotor without molybdate produced a single, sharp receptor peak at 9 S,
suggesting that the native receptor form may be a large complex that is
unstable in vitro and that requires molybdate for its preservation
during lengthy ( ^ 20 h) conventional gradient sedimentation runs
(Grody et al., 1982). It seems paradoxical that steroid receptors
composed of quite distinct polypeptides may form, in the presence of
molybdate (and possibly in vivo), oligomeric complexes sharing nearly
identical hydrodynamic parameters; for example the progesterone receptor
consists of two distinct polypeptide subunits (A = 79,000 daltons and
B = 108,000 daltons; e.g., Grody et al., 1982), whereas glucocorticoid
receptors purified from several different tissues have been found to
contain a single polypeptide (A = 87,000 daltons; e.g., Nordeen et al.,
1981). However, the tetrameric structures that have been proposed for
the native (in vivo) and molybdate-stabilized nonactivated receptor
forms, such as A2B2 (374,000 daltons) for the progesterone receptor
and A^ (348,000 daltons) for the glucocorticoid receptor could possess
very similar sizes and shapes that cannot be distinguished by simple
hydrodynamic measurements. Since estimates of molecular weight derived
from SDS-PAGE and from hydrodynamic parameters do not always agree
exactly, the SDS-PAGE molecular weights listed above for hypothetical
tetrameric complexes are not inconsistent with the hydrodynamic
estimates of 315,000 daltons that we and others have observed.
What is the nature of the slowly-sedimenting (3.7 S) peak "B"
(figure 4-31, table 4-3) that is produced by prolonged sedimentation of

216
the partially-purified 77A steroid-receptor complexes in the continued
presence of 10 mM NagMoO^? Since we have postulated that the large
o
(77A, 9-10 S) complex is a tetramer composed of identical subunits, the
o
3.7 S peak could represent the partial conversion of the 77A tetramer
into the smaller monomers. This proposal is strengthened by our very
recent discovery that the presence of 20 mM molybdate (instead of the
nominal 10 mM concentration in buffer A) during the sedimentation of
3
[ H]TA-receptor complexes in crude cytosol stabilized the 9-10 S peak A
and completely eliminated the slowly-sedimenting peak B, suggesting that
the partial conversion of peak A (9-10 S) to peak B (3.7 S) previously
observed in 10 mM molybdate was probably not a result of proteolytic
o
cleavage of the large complex. (The 77A radius of the large complex was
not altered by the higher molybdate concentration.) In fact, we have
not detected in the presence of molybdate any of the receptor fragments
produced by limited proteolysis and retaining functional steroid binding
sites that have been observed in the absence of molybdate by others
(e.g., Sherman et al., 1978; Wrange and Gustafsson, 1978).
Very recently we have also examined the physiochemical properties
of heat-activated (transformed) mouse brain [ H]TA-receptor complexes in
cytosol that has been adjusted to 20 mM Na^MoO^ following warming to
room temperature (22°C) for a period of 45 min (Luttge and Gray,
unpublished). The activated [ H]TA-receptor complexes were sedimented
in gradients containing 20 mM Na^MoO^, or gel filtered on a column of
Sephcryl S-300 equilibrated with buffer contianing 20 mM Na^MoO^. The
nucleophilic activation of the [ H]TA-receptor complexes effected by the
warming procedure, and the failure of subsequently added 20 mM molybdate
to reverse the activation of receptors warmed in its absence, were

217
confirmed by observing the increased binding of activated receptor
complexes to DNA-cellulose (by a modification of standard methods; e.g.,
Dahmer et al., 1981). In the presence of molybdate the activated
o
receptors sedimented at 3.7 S and possessed Stokes radius 58 A; the
single well-resolved S-300 and gradient peaks (not shown) were
symmetrical and characteristic of a single molecular species having a
molecular weight of 90,000 daltons. These molecular characteristics are
consistent with several reports of the size and shape of activated
glucocorticoid receptors from a variety of sources measured in the
absence of molybdate (e.g., Hutchens et al., 1981; Norris and Kohler,
1981; Stevens et al., 1979; Wrange et al., 1979), suggesting that the
presence of molybdate neither alters the observed hydrodynamic
parameters of the activated receptors nor restores to them the
parameters characteristic of the nonactivated species. Furthermore, the
derived molecular weight (90,000 daltons) of the activated complexes
agrees well with the molecular weight of the proposed single polypeptide
monomer measured by SDS-PAGE (sodium dodecyl sulfate-polyacrylamide gel
electrophoresis; e.g., Nordeen et al., 1981). In further contrast to
the nonactivated receptor complexes, a significant fraction of the
activated receptors aggregated into very high molecular weight species
that eluted from the S-300 columns at the void volume and sedimented to
the bottom of the centrifuge tubes. Thus, receptor activation is
consistent with an alteration that promotes, among other changes, the
dissociation of the proposed native tetramer into its monomeric
subunits. The observed aggregation of a fraction of the activated
receptors in the presence of 20 mM molybdate and .15 M KC1 further

218
suggested that the activation process exposes a hydrophobic domain on
the receptor surface; this suggestion was strengthened by our further
discovery that activation dramatically increased the adsorption of
[ H]TA-receptor complexes by glass fiber filters (Whatman GF/C).
It is thus likely that the slowly-sedimenting peak "B" displayed in
figure 4-31 represents a partial conversion of the (partially-purified)
O
77A complex to activated monomers; the separation of the large complex
from associated low molecular weight substances by S-300 chromatography
may have increased the concentration of molybdate required to prevent
activation during the prolonged sedimentation at moderate ionic strength
(e.g., Leach, Grippo, Housley, Dahmer, Salive and Pratt, 1982). The
o
measured size of the activated receptors (58-60 A) is also in agreement
with the radius of the "nonactivated" receptors measured in the absence
of molybdate, suggesting that the "nonactivated" receptors had probably
become activated during the long incubation without molybdate at 0-4°C
and moderate ionic strength.
Our data suggest that perfused mouse brain cytosol contains a
single population of putative glucocorticoid receptors and,
additionally, a class of CBG-like binders whose source has not been
determined. We have found no evidence to support a popular hypothesis
(e.g., McEwen et al., 1979; Nestler, Rainbow, McEwen and Greengard,
1981) that neurons contain behaviorally-relevant receptors that
preferentially bind corticosterone and cortisol, whereas glial cells may
carry receptors having higher affinity for the synthetic agonists
TA and dexamethasone.

CHAPTER V
THE BINDING OF CORTICOSTERONE TO A CBG-LIKE
COMPONENT OF MOUSE BRAIN CYTOSOL
Introduction
It is often stated that target cell membranes do not present a
barrier to free lipophilic steroids, and that their passage from
extracellular to intracellular fluid compartments is governed solely
by simple diffusion. Recent studies have demonstrated, however, that in
at least several different cell types steroid uptake may involve
carrier-mediated transport in addition to simple diffusion, and
therefore that the ability of a cell to accumulate steroid may be
considerably more complex than the simple uptake customarily attributed
to the intracellular receptors (for review, see: Giorgi, 1980).
Several studies have established that cortisol and corticosterone
are taken up into isolated rat liver cells and purified rat liver plasma
membrane vesicles by processes that have the characteristics of carrier-
mediated transport (e.g., Rao, Rao, Haller, Breuer, Schattenberg and
Stein, 1976; Allera, Rao and Breuer, 1980). The uptake of both steroids
was very rapid (cell uptake of cortisol was far more rapid than cortisol
binding by liver cytosol receptors), highly temperature-sensitive
(reduction of the incubation temperature produced a far greater decrease
in the rate of cortisol uptake into cells than in the rate of steroid
binding to cytosol receptors in vitro), and was saturable and followed
219

220
Michaelis-Menten kinetics. Analysis of initial uptake rates as a
function of steroid concentration revealed the presence of both low and
high-affinity, saturable uptake systems, in addition to a linear, non¬
saturable diffusion component. The specificity of the saturable systems
was examined by competition experiments using unlabeled steroids; the
pattern of results was complex. As expected, corticosterone and
cortisol inhibited both systems competitively; dexamethasone inhibited
both uptake components noncompetitively, as did both estradiol and
testosterone. Biphasic Arrhenius plots relating absolute temperature
and the initial rate of cortisol uptake into cells yielded different
activation energy barriers for the temperature ranges 5-20°C and
20-32°C, whereas the Arrhenius plot for binding to the cytosol receptors
showed a single, lower barrier over the entire temperature range 5-32°C.
Abrupt changes in membrane fluidity caused by lipid phase transitions
(membrane "freezing" or "thawing") known to occur at temperatures near
10°C (e.g., Inesi, Millman and Eletr, 1973) probably contributed to the
dramatic increase in activation energy found below 20°C. Treatment of
the cells with metabolic inhibitors abolished both saturable components,
leaving intact only the linear diffusion process. Thiol group reagents
inhibited the high affinity system, suggesting the involvement of
protein sulfhydryl groups in the uptake mechanism. Cell surface
carbohydrates were also implicated in the saturable uptake of the
steroids into liver cells. There is no obvious explanation for the
reported absence of such a saturable, temperature-dependent uptake
mechanism in hepatoma (HTC) cells, but it is possible that this membrane
transport function may have been lost during the establishment of the

221
transformed cell line in culture (Rousseau, Baxter, Higgins and
Tomkins, 1973).
Another cell type that appears to possess a specific glucocorti¬
coid transport mechanism is the ACTH-secreting mouse pituitary tumor
cell AtT-20/D-l, a well-studied glucocorticoid target cell. The satur-
able uptake of [ Hjtriamcinolone acetonide (TA) by intact tumor cells
was measured at several different temperatures, and the characteristics
of this uptake were found to be different from those of steroid binding
to receptors in cytosol preparations from these cells (e.g., Harrison,
Fairfield and Orth, 1975, 1976; Harrison et al., 1977; Svec and
Harrison, 1981). The steroid specificity of the saturable glucocorti¬
coid uptake process was, however, qualitatively similar to that of the
isolated cytosol receptors (and therefore quite different from that of
plasma CBG, transcortin). When specific initial uptake rates were
measured over a wide temperature range a biphasic Arrhenius plot very
similar to that reported for liver cells (Rao et al., 1976) was obtained
with the pituitary tumor cells; the activation energy for the saturable
uptake process changed abruptly at 16°C, again indicating the presence
of a lipid phase transition that dramatically decreased the mobility of
putative membrane carriers at the lower temperatures. The effects of
several potential inhibitors that do not affect the cytosol receptors or
alter cell viability were also examined. Neuraminidase and phos¬
pholipase A^ almost completely abolished specific uptake, but they had
no effect on the binding of TA to cytosol receptors. Dimethyl sulfoxide
(DKSO), ethanol, and the extracellular sulfhydryl inhibitor PCMPS also
reduced specific TA uptake dramatically. Thus, the specific uptake
mechanism in these cells is sensitive to the loss of sialic acid groups

222
and to other disruptions of normal membrane organization. A saturable,
NAD+-stimulated glucocorticoid uptake mechanism has also been identified
in membrane vesicles prepared from normal human placenta (Farit, Harbison
and Harrison, 1979).
While it is not clear how general this saturable uptake phenomenon
may be (i.e., in regard to other hormones and target cell types), and
while the relative contributions of simple diffusion and specific,
carrier-mediated processes to the overall steroid uptake at
physiological temperatures are also not known, the experiments reviewed
above argue for the involvement of membrane components in specific,
saturable glucocorticoid uptake in at least some cell types.
A CBG-like protein has been found in association with both plasma
membrane and cytosol fractions from perfused whole pituitaries and from
isolated adenohypophysial cells (e.g., Koch et al., 1976; Koch et al.,
1981a; Koch, Sakly, Lutz-Bucher and Briaud, 1981b). This CBG-like
binder shared many physiochemical characteristics with plasma CBG and
also showed the same steroid specificity (i.e., it bound corticosterone
but not dexamethasone); furthermore, like CBG it had negligible affinity
for nuclear or DNA acceptor sites. The locus of synthesis and the in
vivo distribution of the pituitary CBG-like binders are uncertain; they
may be cytoplasmic, and a significant concentration of them may also be
complexed to the inner or outer plasma membrane surface. Strong
evidence has suggested that this macromolecule (when intracellular) can
regulate the binding of natural glucocorticoids to the "true"
glucocorticoid receptors by competing with receptors for the available
intracellular corticosterone, and studies with CBG antisera have
suggested that the CBG-like binders may be involved in the uptake of

223
natural glucocorticoids (but not dexamethasone) into pituitary cells
(e.g., de Kloet, Burbach and Mulder, 1977; Koch et al., 1981a,b).
Although the previously discussed saturable glucocorticoid uptake
mechanism found in AtT-20/D-l pituitary tumor cells does not possess the
steroid specificity characteristic of CBG, these cells have been found
to contain, in addition to the glucocorticoid receptor, an additional
glucocorticoid binding site that is present even in cells cultured in
serum-free media and that is possibly associated with the plasma
membrane; this binding site has much higher affinity for corticosterone
than for dexamethasone or TA and may be related to the CBG-like protein
found in the normal adenohypophysis (e.g., Harrison, Fairfield and
Orth, 1976).
CBG-like proteins have also been found in cytosol fractions
prepared from several other tissues, which include uterus (e.g.,
Al-Khouri and Greenstein, 1980), lung (e.g., Giannopoulos, 1976), liver
(e.g., Suyemitsu and Terayama, 1975; Weiser, Do and Feldman, 1979),
kidney (e.g., Feldman, Funder and Edelman, 1973; Weiser et al., 1979),
heart (Seleznev, Danilov and Smirnov, 1979), skeletal muscle (Mayer,
Kaiser, Mil hoi 1 and and Rosen, 1975), and lymphocytes (e.g., Werthamer,
Samuels and Amaral, 1973); CBG-like binding sites have also been found
associated with liver plasma membranes (Suyemitsu and Terayama, 1975).
Immunoreactive CGB-like material has been detected (with highly specific
antibodies raised against purified rat plasma CBG) in most liver cells,
in many kidney collecting tubule cells, in spleen "white pulp" (con¬
taining lymphocytes), some myometrial cells, in scattered anterior
pituitary cells, and in most posterior pituitary (but no intermediate
lobe) cells from perfused rat tissues (e.g., Siiteri, Murai, Hammond,

224
Nisker, Raymoure and Kuhi*, 1982). These investigators have also
reported a large corticosterone-dependent increase in the uptake of
125
[ I]CBG into rat spleen, kidney and uterine tissue. Furthermore, they
have observed the dramatic, corticosterone-dependent uptake (and
probable nuclear concentration) of FITC-labeled CBG into GH^ pituitary
tumor cells, hepatocytes and lymphocytes (Siiteri et al., 1982).
The observations discussed above have led several groups to suggest
that the intracellular or membrane-bound CBG-like binders are derived
initially from the circulation (i.e., that they are synthesized in
liver), and that they may facilitate the cellular uptake of
corticosterone (e.g., Al-Khouri and Greenstein, 1980; Koch et al., 1981;
Siiteri et al., 1982). Stimulated by the observation that perfused
mouse brain cytosol contains more high-affinity binding sites for corti¬
costerone than for dexamethasone or TA, we have examined the possibility
that the mouse brain may also contain a CBG-like binder in addition to
the putative glucocorticoid receptor. Furthermore, the experiments have
allowed us to further examine the popular hypothesis of glucocorticoid
receptor heterogeneity that has been proposed to explain both the dif¬
ferent patterns of natural and synthetic steroid uptake by the brain and
the different behavioral and neurochemical effects of dexamethasone and
corticosterone that have sometimes been observed (e.g., Bohus and de
Kloet, 1981; Nestler et al., 1981). We have observed that dexamethasone
binds to a subset of the corticosterone binding sites, and that the
remaining corticosterone binding sites have many of the characteristics
of plasma CBG.

225
Materials and Methods
Chemicals, Steroids, Isotopes, Animals, Buffers, and Cytosol Preparation
The sources of supplies and the general methods employed have all
been described in chapter IV, "Materials and Methods."
Binding Assays
3
The principal assay used to measure bound [ Hjsteroid following
equilibrium incubations was the DEAE (Whatman DE-81) filter assay, which
has been described in chapter IV. Some binding data obtained with the
DEAE filter assay were also compared to values obtained with a hydro¬
xyapatite (HAP, Bio Gel HTP) batch assay. This assay was similar to
several used previously to measure the binding of steroids to receptor
proteins (e.g., Walters and Clark, 1977). For each of the triplicate
determinations a 50 1 aliquot of the sample was added to 1 ml of a 50%
suspension of HAP in buffer A. The samples remained in ice, with
occasional vortexing, for 15 min, followed by centrifugation at 2300 x g
for 10 min to pellet the HAP. The pellets were then washed 3 times (by
resuspension with 2 ml buffer A and recentrifugation) over a 30-45 min
period (at 0-4°C), and were then extracted with 2 ml Triton-toluene
scintillation cocktail, which was added to scintilation vials with 8 ml
additional Triton-toluene flúor for the determination of radioactivity
by liquid scintillation. The column and gradient fractions generated by
gel charomatography and sedimentation were assayed, following incubation
with [ Hjsteroid, by adsorption of free steroid with dextran-coated
charcoal as described below.

226
Gel Chromatography and Gradient Sedimentation
The Stokes radii (Rs) of unlabeled plasma CBG and the brain cytosol
CBG-like binder were determined by gel filtration of samples in buffer A
at 0-4°C. Characteristics of the 1.5 x 98 cm Sephacryl S-300 column
have been described in chapter IV. A 2 ml aliquot of the unlabeled
sample (cytosol, approximately 7.5 mg/ml; plasma, diluted 1:10 in
buffer A) was applied to the column, and elution with buffer A was
begun. Following elution, specific CBG-like binding was measured in
each fraction. Pairs of 165 yl aliquots were removed from each 2 ml
fraction and diluted sequentially with 10 yl buffer A containing un¬
labeled dexamethasone to produce a final concentration of 20nM dexa-
methasone and then with 75 yl buffer A containing [ H]corticosterone
(and, for one of each pair, a 200-fold excess concentration of unlabeled
corticosterone) to produce a final [ H]corticosterone concentration of
lOnM. Samples were incubated for 4-6 h at 0-4°C, and free steroid was
then removed by adsorption to dextran-charcoal. The adsorption assay
was performed by adding the 250 yl sample to a 1.5 ml suspension of
dextran-coated charcoal (0.75% Norit A activated charcoal, Fisher;
0.075% Dextran T-70, Pharmacia) in buffer A. Following incubation for 5
min at 0-4°C with occasional vortexing, the charcoal was pelleted by
centrifugation at 1600 x g for 5 min. The supernatant was then taken
for the determination of bound radioactivity by liquid scintillation
counting. Calibration of the column with proteins of accurately known
Stokes radii has been described in chapter IV.
The sedimentation coefficients of plasma CBG and the brain cytosol
CBG-like binder were determined by standard rate sedimentation in
glycerol gradients. Samples (250 yl) of unlabeled diluted plasma (1:10)

227
or brain cytosol (7.5 mg/ml) were centrifuged at 2°C for 25 h at 234,000
x g (average) through 5 ml gradients of 15-35% (w/v) glycerol prepared
in buffer A. The cellulose nitrate tubes were punctured, and 175 yl
fractions were collected. Pairs of fractions from parallel gradients
(which had been loaded with identical samples) were pooled to produce a
series of 350 yl samples, and pairs of 165 yl aliquots were taken from
each of these pooled samples for the assay of specific CBG-like binding
exactly as described above for the determination of specific CBG-like
binding in the S-300 column fractions. The value of S^q w for a peak
was calculated from the linear regression of S2Q w vs. sedimentation
distance (Martin and Ames, 1961) for the standard proteins, which were
run on parallel gradients in buffer A. The apparent sizes and shapes of
the binding sites were determined by standard methods (Siegel and Monty,
1966; Sherman, 1975) as described in chapter IV. The partial specific
volume (v) required for the calculations was assumed to be the value
reported by Westphal (1975) for human, rat, and rabbit plasma CBG
(0.70 cm3/g).
DEAE and Blue A-Agarose Minicolumn Chromatography
Unlabeled samples of perfused mouse brain cytosol or plasma
(diluted 1:40 with buffer A) were chromatographed on Bio-Rad DEAE
Bio-Gel A minicolumns (column characteristics: total volume = 5 ml;
flow rate = 6 ml/h; fraction volume = 1 ml; maintained at 4°C). The
column was washed extensively and equilibrated with buffer A. Samples
were run into the column and washed in with 200 yl buffer A. Binding
was allowed to proceed (30 min), and the column was then washed with

228
25 ml buffer A. Bound substances were eluted by a 50 ml linear gradient
(0-250 mM KC1 in buffer A); fractions (1 ml) viere collected. The con¬
centration of specific CBG-like binding in each fraction was assayed
exactly as described above for the determination of the Stokes radius by
gel chromatography. The elution position of [ H]TA-labeled putative
glucocorticoid receptors in perfused brain cytosol was determined by
chromatographing samples previously equilibrated with lOnM [ H]TA as
described in chapter IV.
The dye Cibacron Blue F-3-GA provides a convenient affinity ligand
for serum albumin, the dominant plasma protein. Since this dye does not
retain CBG or other a- or 6-globulins (e.g., Travis, Bowen, Tewksbury,
Johnson and Pannell, 1976), we have enriched CBG and the CBG-like binder
in diluted plasma and perfused mouse brain cytosol samples by negative
("drop-through") chromatography on blue A-agarose minicolumns (Amicon).
The column (2 ml bed volume) was washed extensively and equilibrated
with buffer A. It was then loaded sequentially, at 10 min intervals,
with six 0.75 ml aliquots of dilute, unlabeled plasma (diluted 1:40 with
buffer A) or unlabeled brain cytosol (2.5 mg protein/ml). The initial
plasma or cytosol sample was spiked with a small amount of [ H]water to
facilitate complete recovery of the sample volume without massive
dilution following its passage through the column. Thus, a 4.5 ml
volume of partially-stripped brain cytosol or albumin-stripped plasma
was recovered by elution with additional buffer A. The partially-
stripped brain cytosol was used to confirm that the blue A-agarose did
not retain the CBG-like binder, and the albumin-stripped plasma was used
in the attempt to measure the concentration of CBG in mouse plasma.

229
Determination of the Contamination of Perfused Mouse Brain Cytosol
by Residual Blood
Because inulin penetrates the blood-brain barrier only very slowly
(e.g., Ferguson and Woodbury, 1969), it may be used to estimate the
contamination of brain tissue by residual blood following perfusion.
Mice were anesthetized with ether and injected via the tail vein with
3y Ci [14C]inulin dissolved in 50 yl saline. Two minutes later a blood
sample (0.5-1 ml) was taken by heart puncture and perfusion with Hepes-
buffered saline (3 ml, pH 7.6) was begun. The duration of perfusion was
approximately 5 min. Brains were removed and homogenized, and cytosol
samples were prepared in buffer A as described in chapter IV. Plasma
samples were prepared by centrifugation. Cytosol and plasma protein
concentrations were measured by a modification of the Lowry method
(Bailey, 1967), and [^4C]inulin radioactivity in triplicate 50 yl
aliquots of cytosol and plasma was determined by liquid scintillation
counting. These measurements were used, in conjunction with an estimate
of the plasma CBG concentration, to estimate the degree of contamination
of perfused brain cytosol by blood-borne CBG.
Equilibrium Binding Experimental Designs and Data Analyses
Experimental designs used to measure equilibrium specific binding
values (B$p) at different ligand concentrations have been described in
chapter IV. When appropriate, ligand affinities and binding site con¬
centrations were determined from Scatchard plots fit to the specific
binding data by linear regression; the affinities of unlabeled ligands
were determined by the Edsall-Wyman competition experimental design
described above in chapters III and IV. Values of specific binding
(B ) were obtained by subtraction of the nonspecific binding (B^) from

230
total bound ligand (By). Individual experimental designs that have not
been described in detail in chapter IV are described below in "Results".
The determination of the affinity of dexamethasone for the receptor
subset of the [ Hjcorticosterone binding sites was determined by gener-
3
ating isotherms with [ Hjcorticosterone as described in chapter IV,
first in the absence and then (using the same cytosol pool) in the
presence of a fixed concentration of unlabeled dexamethasone (the
Edsall-Wyman design). The isotherm generated without dexamethasone was
used to construct a Scatchard plot for the estimation of the total
binding site concentration B^ and a single for the binding of
[ Hjcorticosterone to the complete set of saturable sites. The iso¬
therm generated in the presence of dexamethasone was then used, in
conjunction with these estimates of B^ and and an additional esti-
mate of the total receptor concentration Bq (generated with [ Hjdexa-
methasone for the same pool of cytosol), to calculate the K^. for the
binding of dexamethasone to a subset of the saturable [ Hjcorticosterone
binding sites. The linear "free-receptor" competition plot (e.g.,
figure 4-27) that is useful for the determination of K^. values within
the two ligand-one site context was extended to this very simple special
case of the two ligand-two site problem as described below and in
chapter III. This extension was facilitated by the absence of a signi¬
ficant dexamethasone-CBG interaction and by the observation that the
binding of [ Hjcorticosterone to the complete set of sites (figure 4-12)
was not biphasic. This observation, which agreed with a similar result
obtained with rat pituitary cytosol containing both glucocorticoid
receptors and CBG-like binding sites (e.g., de Kloet, Wallach and

231
McEwen, 1975), suggested that the affinity of corticosterone for CBG-
like binders was similar to its affinity for the putative glucocorticoid
receptors (see also figure 5-2, below, for additional confirmation).
The nomenclature for this special case of the two ligand-two site
problem is the following: By and By are, respectively, the concentra-
tions of specifically-bound [ H]corticosterone and unlabeled dexametha-
sone (i.e., the competitive inhibitor). B^ and Byy are the concen-
trations of [ Hjcorticosterone bound to the putative receptors and to
CBG-like binders, respectively: By = B^ + Byy. B^ is the total
concentration of binding sites, composed of Bq putative glucocorticoid
receptors and T CBG-like binders: BMAV = B + T . K, describes the
' o MAX o o d
3
approximately common affinity of [ H]corticosterone for both the
receptor and the CBG-like binders, and K^. is the equilibrium constant
for the binding of dexamethasone to the glucocorticoid receptors.
3
Fy and Fy are the concentrations of free [ H]corticosterone and un¬
labeled dexamethasone, respectively.
At equilibrium the mass action rate equations for the specific
binding of corticosterone and dexamethasone may thus be written as
(5-1)
{Bo ~ BLR - BC)FC = KdiBC’ and
(5-2)
(5-3)
Equation (5-2) immediately suggests the competition "free receptor" plot
(e.g., figure 5-1, inset) described by the equation

232
(5-4)
where the bound/free ratio refers to the competing dexamethasone.
Equations (5-1) and (5-3) may be combined, using the fact that
(5-5)
which was used to find the abscissa of the "free receptor" plot.
Equation (5-1) may be transformed easily to the expression
Bc = B0 ' [B0 " BLR ' BC’ free sites^1 + FL/Kd^’
(5-6)
which was then used, in combination with the identify F^. = - B^, to
find the ordinate. The line was fit by simple 2-parameter least-squares
linear regression and thus, for statistical reasons, was not constrained
to intersect the origin. The value of was given by the reciprocal
of the slope of the plot.
Results
Equilibrium Binding Parameters for the Mouse Brain Glucocorticoid
Binding Sites
The measured values of the equilibrium binding parameters for
Most of these values have been excerpted from table 4-1 and are repeated
here in a simplified table for convenience. Individual isotherms for

3
Table 5-1. Equilibrium binding parameters for [ H]glucocorticoids in perfused mouse brain cytosol.
The tabulated parameter estimates are x ± s.e.m. Numbers within parentheses indicate either units
of measure or the number of independent experiments that have been averaged. Steroid abbreviations
are defined in the footnotes to table 4-2.
Parameter
[3H]DEX
¿H]B
BQa (fmole/mg)
370 ± 15(43)
360 ± 60(3)
BMAXb (fmole/mg)
—
600 ± 40(15)
Kdc (xlO" 9M)
1.8 ± 0.2(18)
7.6 ± 0.6(3)
Kdd (xl0"9M)
—
6.8 ± 0.6(7)
Kdi[DEX]e (xl0”9M)
—
1.0 ± 0.2(6)
kdi[B] (xl0"9M)
4.7 ± 0.6(4)
—
Cytosol T^ (fmole/mg)
—
230 ± 20(3)
Kdg (x10"9M)
—
4.7 ± 0.3(3)
Hill "n"h
—
0.90 ± .04(3)
a. Bq for putative receptors only; nonspecific correction determined with 200-fold excess DEX for both.
b. Total binding site concentration; nonspecific correction determined with 200-fold excess B.
c. Equilibrium dissociation constants for putative receptors only.
d. Equilibrium constants for complete ensemble of sites.
Continued
ro
CO
CO

Table 5-1 (Continued)
e. Equilibrium constant for the binding of DEX to the receptor subset of the complete ensemble of
3
[ H]B binding sites.
f. CBG-like binder concentration, measured in the presence of 4 yM DEX to block receptors.
g. Apparent K. for cytosol CBG-like binder, measured in the presence of 4 yM DEX to block receptors.
0 3
h. Hill coefficient for the binding of [ H]B to the cytosol CBG-like sites.

235
3 3 3
generated with [ Hjdexamethasone, [ HJTA and [Hjcorticosterone that are
representative of most of the experimental designs have been presented
in figures 4-10, 4-11, 4-12, 4-13 and 4-27, which will now be supple¬
mented with the additional figures 5-1 and 5-2.
3 3
The isotherms generated with [ Hjdexamethasone and [ HJTA were con¬
sistent with a single population of high-affinity binding sites (for
which [ H]TA has higher affinity than [ Hjdexamethasone), and both
ligands produced similar estimates of total receptor concentration (B0).
Isotherms describing the binding of [ Hjcorticosterone to the complete
ensemble of saturable sites in brain cytosol were deceptively consistent
with a single population of binding sites, but the resulting estimate of
total binding site concentration (B^) was significantly greater (63%
3
increase) than the estimates obtained with [ Hjdexamethasone and
3 3
[ HJTA. The "merged" or shared affinity of [ Hjcorticosterone for the
complete set of binding sites was lower (K^ was larger) than the
receptor affinity measured with [ Hjdexamethasone or [ HJTA. Since it
seemed likely that this large ensemble of corticosterone binding sites
contained a subset pool of contaminating plasma CBG or intracellular
CBG-like binding sites that were distinct from the actual glucocorticoid
receptors, separate [ Hjcorticosterone isotherms were also generated by
using 200-fold excess unlabeled dexamethasone to saturate only putative
glucocorticoid receptors (and not any corticosterone-specific CBG-like
binders) in the nonspecific control incubations, thereby removing the
contribution of CBG-like binding sites from the derived values of the
specific binding (B^). The isotherms generated in this way were also
consistent with a single class of non-cooperative binding sites (i.e.,
putative receptors), whose estimated concentration was not different

Fig. 5-1. Representative experimental data (generated by the "Edsal1-Wyman" experimental design and
displayed in the Scatchard coordinate system) used to determine the affinity of dexamethasone
for the putative receptor subset of the complete ensemble of [JH]corticosterone binding sites.
The upper isotherm (-DEX,#) was generated as described in the text and in the legend to figure 4-8, and
the lower curve (+3nM DEX,A) was generated in an identical fashion with the same pool of cytosol, except
that both members of each pair of tubes contained 3 nM unlabeled dexamethasone to affect the "Scatchard"
plot as depicted by competition for the glucocorticoid receptor binding sites. The upper line (•) was
fit by simple linear regression, and the competition curve (A) was fit by quadratic polynomial regression;
the [ H] corticosterone dissociation constant (K^) and total binding site concentration (BMAX) were derived
from the slope and intercept of the upper [3H]corticosterone Scatchard plot (•).
Inset: representative two-ligand, two-site competition "free receptor" plot used to determine the equili¬
brium dissociation constant (K^-) for the binding of unlabeled dexamethasone to the glucocorticoid receptor
subset of [3H]corticosterone binding sites. The points were derived from the data displayed in the Scatchard
coordinate system. The nomenclature of the figure conforms to that of chapter III, with the identification
of L with [ Hjcorticosterone and C with dexamethasone. The plot is described in the text and in detail in
chapter III. The putative receptor concentration (B ) was measured by a separate determination with
3 0
[ H]dexamethasone (not shown), and the abscissa was then calculated by equation (5-5). Equation (5-6)
was used, in conjunction with the known dexamethasone concentration (S^), to find the ordinate, which is
the bound/free ratio for the competing dexamethasone. The line (equation 5-4) was fit by simple uncon¬
strained, 2-parameter linear regression. The reciprocal of its slope is the equilibrium dissociation
constant (K^. or K^) for dexamethasone. For the specific experiment displayed: = 4.9 nM;
B|yjax = 4*6 nM (813 fmoles/mg); Bq = 2.6 nM (453 fmoles/mg); the protein concentration was 5.7 mg/ml,
and the dexamethasone K^. = 0.64 nM (the reciprocal of the slope of the "free receptor" plot).

I.Ch

3
Fig. 5-2. Scatchard plot depicting the binding of [ H]corticosterone to CBG-like binders in perfused
mouse brain cytosol in the presence of 4 yM dexamethasone.
Cytosol was prepared in buffer A, and pairs of samples (250 yl) were incubated for 16 h at 2°C with
increasing concentrations of [ H]corticosterone and, for one of each sample pair, a 200-fold excess of
unlabeled corticosterone. All incubation tubes also contained 4 yM dexamethasone. Triplicate 50 yl
aliquots were then assayed by the DEAE filter method for the determination of total binding (By) and
nonspecific binding Specifically bound steroid (BSp) was determined by subtracting BN<- from By.
The total [^Hjcorticosterone concentration ranged from 0.8 to 44 nM. The line was fit by least-squares
linear regression. Cytosol protein concentration was 7.8 mg/ml. Equilibrium dissociation constant
= 4.3 nM, and CBG-like binding site concentration TQ = 1.9 nM (240 fmole/mg cytosol protein).
Inset: Hill plot (line fit by linear regression) derived from the same specific binding data combined
with the estimate of T& generated by the Scatchard plot. The regression includes points in the region
where binding site occupancy (e = Bsp/T0) does not exceed .8 (80%). The slope of the line provides the
estimated Hill coefficient n = 0.93.


240
3 3
from the estimates obtained with [ Hjdexamethasone and [ HjTA. Thus,
[ Hjcorticosterone bound with comparable affinity both to the gluco¬
corticoid receptors and to an additional class of sites that did not
recognize the fluorinated agonists.
The affinity of corticosterone for the [ H]dexamethasone binding
sites in perfused brain cytosol was measured as described in chap¬
ter IV. The value of ^[B] obtained by combining the replications of
this experiment (4.7 ± 0.6 nM) was comparable to the value determined by
using [ Hjcorticosterone (± 200-fold excess dexamethasone) to label the
receptors directly (7.6 ± 0.6 nM). The discrepancy between these values
of K^. and for the corticosterone-receptor interaction is probably
not unreasonable, since rather different experimental designs were used
to generate them (see chapter IV, "Discussion"). The purely competitive
displacement of [ Hjdexamethasone by corticosterone (figure 4-27)
indicated that corticosterone was an endogenous ligand for the putative
glucocorticoid receptor labeled by [ Hjdexamethasone in brain cytosol.
The affinity of dexamethasone for the receptor subset of the
3
[ Hjcorticosterone binding sites was also measured. Pairs of cytosol
3
samples were incubated with a series of concentrations of [ Hjcorti¬
costerone (± 200-fold excess unlabeled corticosterone) as described
previously for the construction of an equilibrium isotherm. An
additional set of pairs of samples was incubated with the series of
concentrations of [ Hjcorticosterone (± 200-fold excess unlabeled
corticosterone) in the presence of a fixed concentration of unlabeled
dexamethasone. At the conclusion of the 16 h incubation triplicate
samples were taken from each tube for the determination of specific
binding (BSp or B^) with the DEAE filter assay. A representative

241
experiment is depicted in figure 5-1. The isotherm generated without
cold dexamethasone was used to estimate and the "shared" «d for the
binding of [ H]corticosterone to the receptor and CBG-like subsets of
the complete ensemble of saturable sites. The isotherm generated in the
presence of cold dexamethasone was used, in conjunction with these esti¬
mates of B^ and K^, and also an estimate of the receptor concentration
Bq generated with [ Hjdexamethasone, to compute the Kdi- for the binding
of dexamethasone to a subset of the saturable [ Hjcorticosterone sites
as described in chapter III and in "Methods." The high affinity of
dexamethasone for this subset of the [ Hjcorticosterone binding sites
(Kdl-[DEX] = 1.0 ± 0.2 nM) was comparable to the receptor affinity de-
rived from Scatchard plots generated with [ Hjdexamethasone alone.
These data strengthened the evidence that brain cytosol contains two
corticosterone binders, a single class of glucocorticoid receptors and a
class of CBG-like dexamethasone-resistant binders.
The binding of [ Hjcorticosterone to the CBG-like binders in per¬
fused brain cytosol was investigated directly by saturating the putative
receptors with a high concentration of dexamethasone. Pools of perfused
mouse brain cytosol were prepared as described in chapter IV, and pairs
of cytosol samples were incubated with a series of concentrations of
[ Hjcorticosterone (± 200-fold excess unlabeled corticosterone). Addi¬
tionally, all tubes contained 4 yM dexamethasone to saturate fully the
glucocorticoid receptors at all concentrations of [ Hjcorticosterone.
Following the 16 h incubation triplicate samples were removed from each
tube for the determination of specifically-bound radioactivity by the

242
DEAE filter assay. A representative isotherm generated in this manner
is depicted in figure 5-2. The equilibrium binding parameters generated
by these experiments were: total CBG-like binding site concentration
Tq = 230 ± 19 (3) fmole/mg protein; Kd = 4.7 ± 0.3 (3) nM; Hill "n" =
0.90 ± .04 (3); the range of protein concentrations for the different
experiments was 7.8 - 8.3 mg cytosol protein/ml. The high-affinity
CBG-like binder concentration in brain cytosol (T ) determined by this
method agreed precisely with the value determined by subtracting the
Bq for [ Hjdexamethasone from the Bfi^x generated with [vH]corticosterone
for a given pool of cytosol (230 fmole/mg protein). The apparent
affinity of L H]corticosterone for the CBG-like binders in perfused
brain cytosol (determined in the presence of 4 uM dexamethasone) was at
least as high as its affinity for the glucocorticoid receptors,
suggesting an explanation for the inability of a Scatchard plot
depicting the binding of [ Hjcorticosterone to the complete ensemble of
saturable sites to resolve the two classes of binders.
Physicochemical Properties of Mouse Plasma CBG and the Brain Cytosol
CBG-like Binders
Representative examples of gel chromatography (Sephacryl S-300) for
the determination of the Stokes radii, and rate sedimentation for the
measurement of the sedimentation coefficients are depicted in fig¬
ures 5-3 and 5-4. The sedimentation coefficients, Stokes radii, and the
derived molecular weights and shape parameters of the binders from
plasma and brain cytosol are listed in table 5-2. The sedimentation
coefficients and Stokes radii of the binders from the different sources
were identical. The size and shape reported in the table were in
reasonable agreement with reported properties of rat, rabbit and human

Fig. 5-3. Comparison of plasma CBG and the CBG-like binder in perfused mouse brain cytosol by gel
chromatography on a column of Sephacryl S-300 in buffer A.
Unlabeled cytosol samples (2 ml, approximately 7.5 mg/ml) and diluted plasma (2 ml, diluted 1:10 in
buffer A) were chromatographed on a column of Sephacryl S-300 superfine (1.5 x 98 cm) at 12 ml/h in
buffer A. Fractions (2 ml) were collected, and the specific CBG-like binding of [ Hjcorticosterone was
assayed in each fraction as described in "Methods". Distribution coefficients (K^) were calculated from
elution volumes (V ), the void volume (V ) indicated by blue dextran, and the total liquid volume (V-)
c U Q I
marked by radioactive small molecules ([2- H]deoxy(D)glucose): = (V - V )/(V^ - VQ). The column
was calibrated with standard proteins, and the Stokes radii of CBG and the CBG-like cytosol binder
were calculated from regressions of R$ vs. several functions of the standard protein values as shown
in figure 4-30. Means and standard errors from replicates are given in table 5-2.

(xlO~J dpm/fraction)
OD (280 nm)

Fig. 5-4. Comparison of plasma CBG and the CBG-like binder in perfused mouse brain cytosol by rate
sedimentation through glycerol gradients.
Unlabeled cytosol samples (250 yl, approximately 7.5 mg/ml) and diluted plasma (250 yl, diluted 1:10 in
buffer A) were centrifuged at 2°C for 25 h at 234,000 x g (average) through 5 ml gradients of 15-35%
(w/v) glycerol prepared in buffer A. The cellulose nitrate tubes were punctured, and 175 yl fractions
were collected. Pairs of fractions from parallel gradients (which had been loaded with identical samples)
were pooled to produce a series of 350 yl fractions, which were assayed for the specific CBG-like binding
of [ Hjcorticosterone as described in "Methods". Values of S2Q w for the peaks were calculated from the
1 inear regression of S20, vs. sedimentation distance (Martin and Ames, 1961) for the standard proteins,
which were run on parallel gradients as 250 yl samples in buffer A: ovalbumin, 3.6 S; BSA, 4.3 S; IgG,
7.4 S. Standard proteins were [^CH3]-methylated by the method of Rice and Means (1971). Means and
standard errors from replicates are presented in table 5-2.

OVALB BSA IgG
1 \ i
OD (280nm)

Table 5-2. Physical properties of the_CBG-like binders in perfused mouse brain cytosol and plasma.
Values listed are, where appropriate, x ± s.e.m. The number of experiments is shown in parentheses.
See figures 5-3 and 5-4 and "Methods" for details.
Parameter
R$ (xlO”®cm)
S20,w (xlO-^sec-1)
M (daltons)
f/f0 (6=o)
b/a (6=o)
Brain Cytosol CBG-like Binder
46 ± 2(3)
4.1 ± 0.1(8)
72,000 ± 5000
1.70
13:1 (prolate)
Plasma CBG
46 ± 2(3)
4.1 ± 0.1(4)
70,000 ± 5000
1.69
13:1 (prolate)
ro
^4

248
plasma CBG (Westphal, 1975). Thus, the size and shape of the cytosol
CBG-like binders are very similar to those of plasma CBG. We have been
unable to locate published measurements of the size and shape of
purified mouse plasma CBG for comparison with the results presented in
table 5-2, but a similar sedimentation coefficient (4.25 S) has also
been reported for CBG in diluted mouse plasma (Lindenbaum and
Chatterton, 1981).
DEAE chromatography of plasma CBG and the brain cytosol CBG-like
binder was performed as described in "Methods". In contrast to the more
tightly-bound [ H]TA-labeled glucocorticoid receptors (see chapter IV),
the CBG and CBG-like binders found in plasma and brain cytosol were
eluted from the DEAE Bio-Gel A columns at identical positions near the
beginning of the linear salt gradient (0-250nM KC1, not shown),
suggesting both that the binders possessed similar surface charge
characteristics and that they were only weakly associated with the DEAE
Bio-Gel A at the ionic strength of buffer A.
Attempts to Measure the Concentration of Mouse Plasma CBG
The results of our attempts to measure the concentration of plasma
CBG in the ovariectomized-adrenalectomized mouse were quite
disappointing. Initially, we hoped simply to construct equilibrium
isotherms that would reveal the binding affinity of CBG for [ Hjcorti-
costerone and the concentration of CBG binding sites in diluted mouse
plasma; this estimate of the plasma concentration would then be used to
estimate the contribution of blood contamination to the concentration of
CBG-like binders in brain cyt