<%BANNER%>

Molecular Dynamics Study of the Conformational Dynamics of HIV-1 Protease Subtypes A, B, C, and F

Permanent Link: http://ufdc.ufl.edu/UFE0042614/00001

Material Information

Title: Molecular Dynamics Study of the Conformational Dynamics of HIV-1 Protease Subtypes A, B, C, and F
Physical Description: 1 online resource (70 p.)
Language: english
Creator: Mcgee, Terry
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: Chemistry -- Dissertations, Academic -- UF
Genre: Chemistry thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Each year AIDS is responsible for millions of deaths worldwide. One of the major targets in anti-HIV therapeutics is protease inhibition. The HIV protease plays a critical role in the reproductive process of the virus, and its inhibition would prevent the maturation and spread of the virus to neighboring cells. Previous studies have shown that, of approved FDA protease inhibitors, HIV-1 subtype B protease is more responsive to drug therapy than that of subtype C, F or A. Using Molecular Dynamics, we explore how the different sequences of subtypes A, B, C, and F determines their preferred conformation. A better understanding of the dynamic motion of the HIV protease would allow researchers to potentially develop new compounds to fight the HIV-1 subtypes C, F, and A viruses.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Terry Mcgee.
Thesis: Thesis (M.S.)--University of Florida, 2010.
Local: Adviser: Roitberg, Adrian E.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042614:00001

Permanent Link: http://ufdc.ufl.edu/UFE0042614/00001

Material Information

Title: Molecular Dynamics Study of the Conformational Dynamics of HIV-1 Protease Subtypes A, B, C, and F
Physical Description: 1 online resource (70 p.)
Language: english
Creator: Mcgee, Terry
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: Chemistry -- Dissertations, Academic -- UF
Genre: Chemistry thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Each year AIDS is responsible for millions of deaths worldwide. One of the major targets in anti-HIV therapeutics is protease inhibition. The HIV protease plays a critical role in the reproductive process of the virus, and its inhibition would prevent the maturation and spread of the virus to neighboring cells. Previous studies have shown that, of approved FDA protease inhibitors, HIV-1 subtype B protease is more responsive to drug therapy than that of subtype C, F or A. Using Molecular Dynamics, we explore how the different sequences of subtypes A, B, C, and F determines their preferred conformation. A better understanding of the dynamic motion of the HIV protease would allow researchers to potentially develop new compounds to fight the HIV-1 subtypes C, F, and A viruses.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Terry Mcgee.
Thesis: Thesis (M.S.)--University of Florida, 2010.
Local: Adviser: Roitberg, Adrian E.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042614:00001


This item has the following downloads:


Full Text

PAGE 1

1 MOLECULAR DYNAMIC S STUDY OF THE CONFORMATIONAL DYNAMICS OF HIV1 PROTEASE SUBTYPES A, B, C, AND F B y T. DWIGHT MCGEE JR. A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2010

PAGE 2

2 2010 T. Dwight McGee Jr.

PAGE 3

3 To Danielle Haywood and my supportive family

PAGE 4

4 ACKNOWLEDGEMENTS It has been through the love and sacrifice of others that I have been able to obtain so much in my life. I would like to commend Dr. Roitberg for his continuous efforts to make sure that I was equipped with the necessary tools to succeed. I appreciate most of all the patience and understanding that Dr. Roitberg has shown me, which has greatly helped to nur ture my development. I would like to ac knowledge my committee who has not only been instrumental in my development as a scientist but as a person as well. I appreciate your patience and thoughtful advice. I am grateful to Dr. Dunn for his guidance and the opportunity to wor k on a project of su ch magnitude. I appreciate Dr. Fanucci for your advice and positive reassurance of my work and progress. I would also like to extend my thanks to Dr. Merz for challenging me in and out of the classroom and for your willingness to see me succeed. Dr. Horens tein, I appreciate how your classes strengthen my knowledge of biochemistry, which has had a profound impact on my research. I am indebted to Dr. Edwards for his invaluable advice and inspirational messages. You have been a valuable mentor. I would like to acknowledge my parents Terry and Sylvia McGee who have been unbelievably understanding and encouraging in my pursuit of a higher education. Throughout my life, my parents have been a continuous stream of motivation and wisdom. I would like to thank all of my friends and family especially Chelsey Rodgers and Golden Marzett. Finally, I would like to acknowledge my fianc e Danielle Haywood who has been nothing but supportive throughout this entire process. I appreciate most of all your understanding on the de mands which graduate school places on my time and life.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDGEMENTS .............................................................................................................4 LIST OF FIGURES .........................................................................................................................6 LIST OF ABBREVIATIONS ..........................................................................................................9 ABSTRACT ...................................................................................................................................10 CHAPTER 1 INTRODUCTION ..................................................................................................................11 1.1 HIV 1 Epidemic ............................................................................................................11 1.2 Genetic Variability ........................................................................................................11 1.3 HIV 1 Genome ..............................................................................................................12 1.4 HIV 1 Life Cycle ..........................................................................................................13 1.4 HIV 1 Protease Structure and Mechanism ....................................................................14 2 THEORY AND METHODS ..................................................................................................17 2.1 Molecular Dynamics .....................................................................................................17 2.2 Molecular Mechanics ....................................................................................................19 2.3 Generalized Born Model ...............................................................................................20 3 MOLECULAR DYNAMIC STUDY OF THE CONFORMATIONAL DYNAMICS OF HIV 1 PROTEASE SUBTYPES A,B,C,F .............................................................................21 3.1 Introduction ...................................................................................................................21 3.2 Methods .........................................................................................................................22 3.3 Results ...........................................................................................................................24 3.3.1 Comparison of the Flap Dynamics ....................................................................24 3.3.2 Comparison of the Three Initial Structures in Subtypes B and Subtypes C .....48 3.3.3 Comparison between the Different Subtypes ...................................................55 3.4 Conclusions .......................................................................................................................64 LIST OF REFERENCES ...............................................................................................................66 BIOGRAPHICAL SKETCH .........................................................................................................70

PAGE 6

6 LIST OF FIGURES Figure page 11 Schematic diagram of the HIV 1 Genome. ........................................................................12 12 A schematic depiction of the life cycle of HIV .................................................................16 31 Representation of the initial x ray crystal structures used in the MD simulations. ...........23 32 Representation of a closed structure, semi open conformation and wide open conformation. .....................................................................................................................24 33 Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype A ...........................................................................................................................25 34 Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of Subtype A. .........................................................................................................................26 35 Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype B (1HHP). ............................................................................................................28 36 Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of Subtype B (1HHP). ............................................................................................................29 37 Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype B (2BPX) .............................................................................................................31 38 Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of Subtype B (2BPX). ............................................................................................................32 39 Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype B (1OHR). ............................................................................................................34 310 Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of Subtype B (1OHR). ............................................................................................................35 311 Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype C (2R8N) ..............................................................................................................37 312 Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of Subtype C (2R8N) ..............................................................................................................38 313 Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype C (2R5P) closed conformation.. ..........................................................................40 314 Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of Subtype C (2R5P). .............................................................................................................41

PAGE 7

7 315 Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype C (2R5Q). .............................................................................................................43 316 Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of Subtype C (2R5Q). .............................................................................................................44 317 Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype F (2P3C) .............................................................................................................46 318 Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of Subtype F (23PC) ...............................................................................................................47 319 Histogram of the distance between ILE50 and ILE50. Comparison of the Subtype B simulations .........................................................................................................................49 320 Histogram of the distance between VAL82 and VAL82. Comparison of the Subtype B simulations. ....................................................................................................................49 321 Histogram of the distance between LYS55 and LYS55. Comparison of the three B subtype simulations. ...........................................................................................................50 322 Histogram of the distance between the ILE50 and THR80 and vice versa. Comparison of the three subtype B simulations ................................................................50 323 Histogram of the distance between ILE50 and Asp25 of each monomer. Comparison of the three subtype B simulations. ....................................................................................51 324 Histogram of the distance between ILE50 and ILE50. Comparison of the three Subtype C simulations. ......................................................................................................52 325 Histogram of the distance between VAL82 and VAL82. Comparison of the three subtype C simulations. .......................................................................................................53 326 Histogram of the distance between LYS55 and LYS55. Comparison of the three subtype C simulations. .......................................................................................................53 327 Histogram of the distance between ILE50 and THR80 and ILE50 and THR80. Comparison of the three subtype C simulations. ...............................................................54 328 Histogram of the distance between ASP25 and ILE50 and ASP25 and ILE50. Comparison of the three subtype C simulations. ...............................................................54 329 The atomic fluctuations of the C Comparison of subtypes A, B, C, F ...........................56 330 Histogram of the distance between ILE50 and ILE 50. Comparison of the different subtypes ..............................................................................................................................57

PAGE 8

8 331 Histogram of the distance VAL82 and VAL82. Comparison of the different subtypes. .............................................................................................................................58 332 Histogram of the distance between LYS55 and LYS55. Comparison between the different subtypes ...............................................................................................................59 333 Histogram of the difference between ILE50 and THR80, ILE50 and THR80. Comparison of different subtypes. .....................................................................................60 334 Histogram of the distance between ASP25 and ILE50 of each monomer. Comparison of the different subtypes. ....................................................................................................61 335 Contour plot of the Root Mean Squar ed Deviation of the closed conformation versus the ILE50 and ILE50 C .. ................................................................................................62 336 Contour plot of the Root Mean Squared Deviation of the closed conformation versus the LYS55 and LYS55 C .. .............................................................................................63 337 Potential new region for protease inhibition. The residues highlighted in blue are 40 43 and 5961 of each monomer. ........................................................................................65

PAGE 9

9 LIST OF ABBREVIATION S AIDS Acquired Immune Deficiency Syndrome ARG Arginine ASP Aspartate EPR Electron Paramagnetic Resonance FDA Federal Drug Administration GB Generalized Born GLU Glutamate GLY Glycine gp Glycoprotein HIV Human Immunodeficiency Virus ILE Isoleucine LYS Lysine MD Molecular Dynamics MM Molecular Mechanics NMR Nuclear Magnetic Resonance PDB Protein Data Bank RMSD Root Mean Squared Deviation THR Threonine WHO World Health Organization UNAIDS Joint United Nations Programs on HIV/AIDS

PAGE 10

10 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science MOLECULAR DYNAMIC S STUDY OF THE CONF ORMATIONAL DYNAMICS OF HIV1 PROT EASE SUBTYPES A, B, C, and F By T. Dwight McGee Jr December 2010 Chair: Adrian E. Roitberg Major: Chemistry Each year AIDS is responsible for millions of deaths worldwide. One of the major targets in anti HIV therapeutics is protease inhibition. The HIV protease plays a critical role in the reproductive process of the virus, and its inhibition would prevent the maturation and spread of the virus to neighboring cells. Previous studies have shown that, of approve d FDA protease inhibitors, HIV 1 subtype B protease is more responsive to drug therapy than t hat of subtype C, F or A Using Molecular Dynamics, we explore how the different sequences of subtypes A, B, C, and F determines their preferred conformation. A b etter understanding of the dynamic motion of the HIV protease would allow researchers to potentially develop new compounds to fight the HIV 1 subtypes C, F, and A viruses.

PAGE 11

11 CHAPTER 1 INTRODUCTION 1.1 HIV 1 Epidemic Human Immunodeficiency Virus (HIV) is a lenti virus, which is responsible for causing Acquired Immunodeficiency Disease Syndrome (AIDS)1. Recent advances in antiretroviral therapy have improved the life expectancy of those infected but have had little impact on controlling the spread of the HIV virus. The World Health Organiz ation (WHO) considers AIDS a pandemic. According to data provided by the Joint United Nations Progr am on HIV/AIDS (UNAIDS) and WHO, an estimated 33.4 million people are currently living with the disease as of 2008. SubSaharan Africa accounts for 22.4 million of the worlds HIV population. In 2008, a pproximately 2 million deaths were due to AIDS and 1.4 million of t otal de aths were in Sub Saharan Africa. This startling fact can be attributed to the inability of these countries to aff ord antiretroviral treatment, lack of education, social stigmatism and etc 1.2 Genetic Variability The high genetic va riability of HIV can be attributed to the activity of the enzyme reverse transcriptase, which will be discussed in later sections. HIV can be divided into HIV 1 and HIV 2. HIV 1 can be divided into groups M main, N nonM/nonO, O outlier and the new ly discovered P2 3 4 5. Group M is the largest and accounts for the majority of infections. This group is further segregated into subtypes A D, F H, J, K and circulating recombinant f orms (CRF) such as CRF01 _A E2. The subtypes relationships and classifications were based on sequence alignments of gag, pol, and env regions2 6 7. Subtype A is predominant in West and Central Africa. Subtype B is dominant in North and South America, Europe and Australia Subtype C can be found in Southern and East Africa, and throughout Eastern Asia. Subtype D is l imited mainly to Central Africa Subtype F is generally

PAGE 12

12 found in Sout h America and Central Africa. Subtype H has been seen only in Central Africa and subtype J in Central America. Lastly, subtype K has only been observed in the Congo and Cameroon. Subtypes A, B, C, and D account for the majority of infections worldwide. Subtype C accoun ts for the high est percentage of those with HIV8. However, i t has been noted that those persons infected with subtype D develop AIDS at a much faster rate and have a higher mortality rate9. 1.3 HIV 1 Genome HIV is ~120 nm in diameter and has a spherical shape. It is compr ised of two copies of single stranded RNA enclosed by the viral protein p24 (matrix) Its genome is rather small and is ~9.4 K b in length. The gag gene encodes the structural proteins matrix ( MA ) capsid ( CA ) and nucleocapsid ( NC ) The two envelope prote ins g41, gp120 are encoded by the env, which is responsible for viral tropism. The pol gene encodes for the three enzymes, reverse transcriptas e, integrase and protease. The function and importance of these enzymes will be discussed in later sections of this chapter. The other genes rev, nef, vpr, vpu, vif, and, tat encode for the six accessory proteins Three of the accessory proteins tat, rev, and vif play a role in the replication of the virus10 11. The other three accessory p roteins vpr, nef, vpu play a role in regulating viral promoters, acting as a negative regulatory factor for viral expression and promoting the CD4 degradation and viral release12 13. Figure 1 1. Schematic diagram of the HIV 1 Genome. Ac cessed and adapted on July 2010 f rom http://www.yale.edu/bio243/HIV/genome.html

PAGE 13

13 1.4 HIV 1 Life Cycle In general, the surface glyc oproteins of enveloped viruses have an essential role in viral invasion of host cells The Human Immunodeficiency V irus type 1 (HIV 1) envelope glycoprotein ( gp) consists of two nonc ovalent subunits gp120 and gp41. First, gp120 is responsible for viral tro pism by binding to target cell receptors and gp41 directs fusion between cellu l ar and viral membranes14 15. gp 120 binds to the CD4 receptor and the CCR5 or CXCR4 co receptors which belong to the chemokine receptor family14. Macrophage (M tropic) strains of HIV 1 use the CD4 and CCR5 receptors as a means to gain access to the cell16. In contrast, T tropic str ains use the CD4 and CXCR4 receptors to gain cell entry16. These receptors can be found present in such cells as T lymphocy tes and macroph ages. The interactions between gp120 and g41 are altered by a conformational change that occurs when gp120 binds to the CD4 receptor and the chemokine receptor17. These changes allow the virus to inje ct its viral genome into the host through fusion. Soon after entry, the process of reverse transcription occurs in which the enzyme reverse transcriptase transcribes a comple me ntary double stranded DNA molecule from a single stranded RNA genome The process of reverse transcription is very error prone and results in mutations due to its in accuracy As a result, these mutations allow for drug resistance. The high frequency of mutation is a direct result of having an average error of 3x105 per nucleotide base per cycle18. The newly form ed DNA is then transported to the nucleus of the cell where it is integrated into the host DNA by an enzyme known as integrase. Inclusion of the virus genetic material into the host cell genome results in the viral DNA becoming a provirus19. The provirus is then transcribed into mRNA, which is further spliced into smaller pieces. This allows it to be tran sported to the cytoplasm where it is translated into the Tat and Rev proteins. The Tat protein allows for increased transcription of proviral DNA20. The Rev protein binds to the unspliced mRNA and allows them to leave the nucleus, which allows for the translation of

PAGE 14

14 the pol, env, and gag genes19. The last and final step of the HIV life cycle is assembly and budding. The protease enzyme is responsible for cleaving the gag and gag/pol which is vital for viral maturation21 22. The structural proteins matrix (MA), capsid (CA), nucleocapsid (NC) are derived from the gag precursor. The pol produces such enzymes as reverse transcriptase, integrase and protease. 1.4 HIV 1 Protease Structure and Mechanism A protease is an enzyme that directs proteolysis and cleaves the peptide bonds that link am ino acid to form polypeptide chains. Proteases are divided into several groups: serine, theronine, cysteine, aspartyl metallo, and glutamic23. HIV protease is classif ie d a s an aspartyl protease because it has two aspartic residues in the active site and substitution of the a spartic residue leads to a loss of catalytic ability24. HIV protease is able to cleave the peptide bonds between TYR/PHE and PRO residu e s and no other enzyme in humans shows the same specificity23. As describe d in earlier sections the protease plays an essen tial role in the life cyc le of HIV and inhibition of its function would re sult in an immature, noninfectious viral particle. The three dimensional structure of HIV protease was not determined until 198925 26. It is composed of two identical monomers each containing 99 amino acid residues which give r ise to a symmetrical homodimer26. Each m onomer has one small helix a nd a four stranded sheet which are formed by the N and C terminal strands23. The active site is located at the interface of the two monomers where each monomer contributes the sequence Asp25Thr26Gly2726. These active site residues are known as the catalytic triad The active site loops are held together by a conformation known as the firemans grip. It is a conformation in which the amide group of each Thr26 monomer donates a hydrogen bond to the opposing Thr26 carbonyl. Furthermore each individual loop is stabilized by the hydrogen bond between O 1 of the aspartate and the

PAGE 15

15 amide group of Gly2726. The active site is covered by flexible flaps, which open to allow the substrate to enter and leave. In the apo form, the flaps populate a conform ation known as semi open; computational studies have simulated flap opening s as wide as 32 angstroms27. HIV p rotease cleaves its substrate through a general acid/base mechanism. The flaps open and allow the substrate to enter and close in order to secure the substrate in the active site. I t has been proposed that the flaps are held in a closed conformation by the presence of a water molecule through hydrogen bonding of the amide group of Ile5028. Plots of the rate vs. pH done by Meeks et al. reveal a bell shape d curve, indicating that one Asp acts as acid and the other as a base29 28. The mechanism proposed by Meeks et al. is that Asp25 accepts a proton (acting as base) from water. The newly formed nucleophile is very potent and attacks the carbonyl of the substrate. The tetrahedral intermediate is stabilized by the carbonyl oxygen accepting a hydrogen from Asp25 (acting as an acid). The Asp25 accepts the hydrogen back from the oxygen as it begins to reform its double bond with the carbon. Simultaneously the carbonyl is reformed as the N C bond begins to elongate and eventually br eaks as the nitrogen accepts a hydrogen from the Asp2529. The catalyst is regenerated, the flaps open and the product leav es

PAGE 16

16 Figure 1 2. A schematic depiction of the life cycle of HIV. Accessed and adapted on July 2010 from http: //www.aidsinfonet.org/

PAGE 17

17 CHAPTER 2 THEORY AND METHODS 2.1 Molecular Dynamics The first molecu lar dynamics (MD) simulation was published by Ald er and Wainwright in which they reported on the interactions of hard spheres30. The f irst protein simulation was performed on the bovine pancreatic trypsin inhibitor paving the way for the application of MD to biological systems31. Molecular Dynamics has proven useful in validating experimental results, structure refinement, dr ugdesign, enzymatic reactions, etc. Molecular Dynamics is based on Newtons laws of motion, particularly his second law, which states that F=ma, where F is the force exerted on the particle, m is it s mass and a is its acceleration. Integration of the equations of motion yields a trajectory I n order to calc ulate a trajectory the initial positions velocities and accelerations must be known. For instance, the initial positions can be gathered from an x ray crystal structure the velocities and the acceleration are determined by the gradient of the potential energy function32 33. The integration of the equations of motion can be easily solved analytically for such systems as a one dimensional harmonic oscillator. On the contrary, this is not feasible for such complex systems as proteins and these equations must be solve d numerically34. Many numerical algorithms have been developed in order to accomplish this, for example, V erlet, leap frog, verlocity V erlet and Beemans35 36 37 38. All of the algorithms use a Taylor series expansion to make the approximation about the positions, velocities and acceleration As stated above th e leapfrog algorithm is commonly used : 1 2 qttqtvttt (2 1) 11 () 22 vttvttatt (2 2)

PAGE 18

18 in which q and v correspond to the coordinate and velocity vectors of all the atoms36. The acceleration is determined from the forces and masses of the atoms. In the leapfrog algorithm the velocities are fi rst calculated at the time (t t) and the positions are determined from the velocities previously calculated. Thus the velocities leap over the positions and the positions leap over the velocities. The advantage of this method is the velocities are explicitly calculated but the drawback of this method is that the calculation of the positions and velocities are deduced in the same step. Langevin Dynamics are often used in conjunction with implicit solvation models. The Langevin equation of motion is a stochastic differential equation in which two force terms have been added to Newtons second law of motion in order to account for the omitted degrees of freedom. In the description of stochastic dynamics the force, which a particle it sees can be attributed to three different factors. The first force felt by a particle depends on its position relative to the other particles32. The second force is described as the force felt by a particle as it moves through the solvent and can be equated to the frictional drag on the particle due to the solvent32. The last contributing factor is the force that a particle experiences due to random fluctuations, which are created through interactions with solvent molecules32. The Langevin Equation can be expressed as: mid2x dt2 Fixi( t ) idxidt mi Ri( t ) (2 3) where m is the mass, x is the position, F is an interaction force between a particle and other particles, represents the collision frequency, and R(t) is the force on the particle due to random fluctuations by interactions with solvent molecules32.

PAGE 19

19 2.2 Molecular Mechanics Molecular Mechanics (MM) makes the assumption that interactions within a system can be described by such processes as bond stretching, bond angl es and rotations about a bond32. Furthermore, the parameters calculated from small molecules can be translated to describe larger systems such as proteins34. An illustration of what parameters are involved in a force field: V rN ki2 Bondsl lo 2 k2 Angleso 2 Vn2 Torsions1 cos n 4ijijrij 12ijrij 6 qiqj4 orij j i 1 Ni 1 N (2 4) where the first three terms describe the covalent interactions and the last two terms describe the noncovalent interactions. V denotes the potential energy, which is function of the positions (r) of N atoms32. The first two terms in Eq. (23) describe energy changes that occur when the bonds and angles deviate from their reference value. In addition kl and k are the respective force constants for the bond and angles The third term in equation 24 describes the torsional angles. The torsional term is expressed in a Fourier series in which Vn is the dihedral force constant, n is the dihedral periodicity, is the torsional angle and is a phase of the dihedral angle 39. The fo urth and fifth terms of Eq. (24) are Lennard Jones and Coulomb potentials. The LennardJones potential is used to describe the van der Waals interactions whereby is the depth of the potential well, is the distance at which the interparticle potential is zero, r12 is the repulsive tern and the r6 is the attractive term. The Coulo mb potential is used to describe the el ectrostatic interactions where q1 and q2 are the charges of atoms, r describes the interparticle distance, and is the electric constant.

PAGE 20

20 The force field ff99SB was used for the parameters of our system39. The ff99SB has better parameters for the backbone torsion terms and the Gly residu es, which are crucial due to the number of Gly residues found in the flap region of the protease27. 2.3 Generalized Born Model Implicit solvation is modeled as a continuum solvent instead of explicitly and is used to estimate the free energy of solutesolvent interactions. Implicit solvation has several attractive advantages. First, the computational cost associated with the use of these models in MD simulations is generally cheaper than the cost of representing water explicitly. Se condly, due to the absence of viscosity associated with explicit water environment the molecule can explore the available conformational space much faster40. The GB model omits the viscous effect of solvent and thus Langevin Dynamics must be incorporated in order to compensate. O ne disadvantage of the Generalized Born Model (GB) is that it over stabilizes salt bridges41 42. GB is an approximation to the PoissonBoltzman equation40. The GB equation can be expressed as: GGB 1 2 1 1 qiqjf rij, aij j 1 Ni 1 N (2 5) f rij, aij rij 2 aij 2e D (2 6) aij aiaj D rij2 aij 2 (2 7) where is the dielectric constant, q represents the charge, ri j is the interparticle distance and aij is the Born radii.

PAGE 21

21 C HAPTER 3 MOLECULAR DYNAMIC ST UDY OF THE CONFORMAT IONAL DYNAMICS OF HI V 1 PROTEASE SUBTYPES A,B,C,F 3.1 Introduction The HIV protease has become an attractive target for drug design due to its role of cleaving the gag and gagpol polyprotein precursors. Furthermore, inhibition of the proteases natural biological function would prevent the maturation of the HIV, hence preventing the infection of neighboring cells. The flap domain has been highly studied and through NMR and crystallographic studies has been shown to exist in numerous conformations T he flap domain is the most mobile of all domains, largely attributed to the number of Gly residues found in this region43. Many different experimental and theoretical studies have been conducted in order to gain a better understanding of the movements of the flaps and how they correla te to drug resistance. Galiano et al. first proposed the used of site directed spinlabels (SDSL) and EPR studies as a means to gain insight on how the mutations impacted the flap dynamics44 45. NMR studies done by Ishima et al. suggest a working model of the flapopening mechanism43. Through the use of MD, Scott and Schiffer proposed the curling of the flaps as mechanism of drug resistance46. Hornak et al. and Boric et al. were both able to successfully simulate the closing of the flaps by placing a ligand into a protease in which the flaps were originally open47 48. Hornak et al. was the first to simulate an opening and reclosing of the flaps27. As previously stated, due to the importance of the flaps having to open and close in order for catalytic activity to occur it has been suggested by previous works that the development of a new class of protease in hibitors that instead target the flap domain or other es sential domains might be more effective than the original idea of developing a protease inhibitor that work s

PAGE 22

22 through competitive inhi bition27 49 50. The effectiveness of inhibitors that competitively bin d to the active site is shortlived due to mutations, which decrease the potency of the inhibitor. While there is a wealth of research available on s ubtype B, few theoretical studies have been conducted on subtypes A, C, or F51. Likewise of the HIV 1 protease inhibitors approved by the Federal Drug Administration (FDA) none ha ve been specifically designed for nonB subtypes. The use of computational techniques such as MD has proven useful in elucidating and confirming the ma i n different HIV protease conformations. In this current study we investigate conformational dynamics of the flaps, and the size of the active site in order to correlate how the sequences of subtypes A, B, C, and F allow for different conformations of the protease. Our results offer insight and suggestions, which might prove to be useful in the development of new protease inhibitors. 3.2 Methods The starting structures of subtype B proteases were obtai ned from the Protein Data Bank (PDB ID 1HHP) semi open conformation, (PDB ID 1OHR ) complexed with nelfinavir and (PDB ID 2BPX) complexed with indinavir52 53 54. The three proteases of su btype C were obtained from PDB (PDB ID 2R8N) open conformation, (PDB ID 2R5P) complexed with prote ase inhibitor indinavir, (PDB ID code 2R5Q ) complexed with the protease inhibitor nelfinavir55 56. S ubtype F protease (PDB ID code 2P3C ) complexed with TL 3 protease inhibitor, and subtype A (PDB ID code 3IXO ) closed conformation, were gathered from the PDB57 58. In the case of the proteases, which were complexed with the inhibitors, the inhibitors were removed prior to simulation. Figure 3 1 shows the structures, whic h were used in the eight simulations of subyptes A, B, C, and F. Prior to the simulation three mutations were made in subtype C in order to revert back to the original sequence K7Q, I63L, and I33L. One mutation was made in subt ype F K7Q. These mutations were originally made to the sequence in order to increase

PAGE 23

23 stability56 57. Only one of the catalyt ic Asp25 was protonated. The m issing heavy and hydrogen atoms of each crystal structure were added by the Leap module of A MBER 11.059. The minimizations and molecular dynamics were performed using the sander and pmemd modules of AMBER. The initial parameters for the protein were gathered from the force field ff99SB39. The solvation was implicitly modeled using Generalized B orn approach (GB) The SHAKE algorithm was used in order to constrain all bonds to hydrogens a nd the timestep was 1 fs In order to control temperature Langevin Dynamics was implemented in which the collision frequency was 1 ps1. During equilibration, each system was minimized and slowly heated up from 50 to 300K with restraints first on hydrogen atoms then all heavy, and backbone atoms. Each system was relaxed for 1ns. In the case where mutations were introduced prior to starti ng equilibrations process, the s ystem was allowed to relax for 1.2 ns. Restraints were removed entirely during the last step of equilibration in order to observe the stability of the system. The production phase consisted of running the equilibrated struct ures at ten different initial velocities for 22ns each and the temperature remained at 300K throughout. Figure 3 1. G raphic representation of the initial x ray crystal structures used in the MD simulations. The first row in re d from left to right 1OHR, 1HHP, and 2BPX which is Subtype B The second row from in gree n from left to right 2R5Q, 2R8N, and 2R5P which is subtype C The last row from left to right 3IXO subtype A and 2P3C subtype F

PAGE 24

24 3.3 Results The next three sub sections contain results anal yzed from the eight different simulations. In the first section we compare the dynamics between a closed, semi open, and proposed wi de open conformation. The second section is a comparison of the three different subtype B and C simulations amongst themselv es. The last section will be a comparison of subtypes A, B, C and F. 3.3.1 Comparison of the Flap Dynamics The results shown below not only compare the flap dynamics each of the ten different simulations of eight structures but their stability as well As previously stated, each of the simulations was compared against three s tructures as shown in figure 32, where the flaps were either closed, semi open and a proposed wide open structure. The coordinates for the semi open structure were derived from 1HH P. The coordinates for the wide open structure were taken from a snapshot of the 1HHP simulation in which a wide open conformation was observed. The closed struct ure u sed as a reference for the Subtype A simulation and Subtype F simulation was 3IXO and 2P3C. The closed struc ture s used for the Subtype C simulations were 2R5Q and 2R5P. The Subty pe B simulations used 1OHR and 2BPX as its reference for a closed structure. Figure 3 2. From left to right, is representation of a closed structure, semiopen conformation and wide open conformation.

PAGE 25

25 Figure 3 3. Illustrates the Root Mean Squared Deviation of the C versus time of ten different simulations of S ubtype A (PDB ID 3IXO) closed conformation. The first frame of each simulation was used as the reference.

PAGE 26

26 Figur e 3 4. Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of each monomer versus time for the ten different simulations of Subtype A. The red was vers us the closed conf ormation The green was versus the semi open conform ation and the crystal structure ( 1HHP ) The blue was versus the (fully) wide open conformation.

PAGE 27

27 Figure 3 3 shows how each of the ten different simulations of subtype A differ from the first frame of their respective simulations. On average each of the ten different simulations fluctuate s be tween 1 and 4.5 angstroms. The large deviations in Figure 3 3 can more than likely be attributed to the movements of the flaps and not as much to the backbone In addi tion, these deviations are indicative of the flaps inverting or for example going from close d conformation to an open conformation. Figure 3 4 shows how the flaps residues, which were considered to be 4358 and 43 58 of each monomer, deviate against the three conformations. As proposed by Hornak et al., when a ligand is not bound, the flaps are most likely to be in a semi open conformation27. This hypothesis is not entirely correct because in the simulations of subtype A the lowest fluctuation only gets within 2.5 angstroms of a semi open con formation. However, subtype A does come within .91 angstroms of the closed conformat ion during several points of the simulation. There were three simulations ig1 ig2 and ig9 in whic h the closed conformation is the predominant orientation of the flaps, as shown in Figure 34. These two simulations demonstrate a preference to the closed conformation throughout the entire simulation. One trend that is observed in Figure 34 is that the flaps are more likely in a conformation that resembles closed or semi open rather than wide open conformation, which is rarely observed. There are points of the dynamics when neither of the three reference structures can be said to exist. The structures are believed to be either the tucked or curl ed structures as proposed by Kear et al60. In the simulations of ig2, ig6 and ig10 we do observe conformations, which get as close to 4 angstroms of the wide open conformation. The results in Figure 3 4 do coincide with the argument made by Layten et al. although they ran MD simulations using subtype B, that the wide open conformation is only a minor component of the structures sampled during dynamics61.

PAGE 28

28 Figure 3 5. Illustrates the Root Mean Squared Deviation of the C versus time of ten diff erent simulations of Subtype B (PDB ID 1HHP) semi open conformation. The first frame of each simulation was used as the reference.

PAGE 29

29 Figure 3 6. Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of each monomer versus time for the ten diff erent s imulations of Subtype B (1HHP) semi open conformation. The red was versus the closed co nform ation The green was versus the semi open conformation. The blue was versus the (fully) wide open conformation.

PAGE 30

30 Figure 3 5 shows deviations of Subtype B versus the first frame of the ten different simulations in which the starting coordinates were gathered from 1HHP. Deviations are seen on average between 1 and 5 angstroms. The ig10 simulation shows the highest fluctuations, which are observed around 5000 ps T he fluctuation become s almost as high as 6 angstroms and the n return s back to 2 angstroms, which is a clear indication that a conformational change must have occurred. In Figure 3 6, as stated earlier we do see that the preferred conformation is semi open. For instance, in simulations ig1, ig2, i g3 and i g7, we observe that the dynamics become as close or below 1 angstrom on several occasion s to the semi open conformation. However there are some instances when the dynamics do become as low as 1 angstrom to the closed conformation but are rarely seen. The simulation ig5 in Figure 36 exhibits a unique and interest ing trend. In the beginning the ig5 simulation favors the semi open conformation but early in the simulation we see a switch in the dynamics that favors neither the semi open or closed conformations T he ig9 simulation in the beginning appears to favor neither the closed, semi open or wide open conformations. However, towards the end of the ig9 simulation we do see that dynamics favor a closed conformation. In these cases the flaps are exhibiting either a tucked or curled conformation. The wide open conformation is seen in the ig10 simulation around 5000 ps but only for a brief moment. This correlates strongly as to why the peak in the ig10 simulation of Figure 3 5 i s present. As previously stated the wide open conformation does not make up a significant portion of the dynamics sampled. There are more instances where the dynamics of 1HHP favors the wide open conformation than seen in the other two subtype B simulations which will be discussed later in this chapter.

PAGE 31

31 Figure 3 7. Illustrates the Root Mean Squared Deviation of the C versus time of ten diff erent simulations of Subtype B (PDB ID 2BPX) closed conformation. The first frame of each simulation was used as the reference.

PAGE 32

32 Figure 3 8. Root Mean Squared Deviation of the flap residues 4358 C and 43 58 C of each monomer versus time for the ten different simulations of Subtype B ( 2BPX) closed conformation. The red was versus the closed conforma tion The green was versus the semi open conforma tion and the crystal structure The blue was versus the (fully) wide open conformati on.

PAGE 33

33 In the simulations gathered from the initial coordinates of 2BPX, deviations are observed between 1 and 3.5 angstroms in Figure 37. In the ig3 simulation the fluctuations quickly rise to 3.5 angstroms after the first few picoseconds and remains there throughout the entire simulation. This large fluctuation is caused by the flaps orienting the mselves in a structure that looks semi open and then quickly converting to a structure that favors more of a closed conformation. Simulations ig4 and ig10 fluctuate the least, where the highest deviation i s seen around 2.5 angstroms. In Figure 3 8 an interesting trend is observed. T he semi open conformation is not the overall dominant form of the flaps as seen in previous figures However, in the ig4 and ig6 simulations the semi open conformation is the dom inant form. In the ig4 simulation, the dynamic s fluctuate consistently between 1 and 2 angstroms from the semi open conformation. T he fluctuations in the ig10 simulation become as close as 1 angstrom in certain point s of the simulation. However, for the case of the ig2 ig8 and ig9 simulations the cl osed conformation appears to be the preferred form. The dynamics of ig3 simulation appear to favor the semi open conformation but then quickly changes to favor either the tucked or curled conformation. The other simulations equally populate either the close or semi open conformation. In general, very few of the simulations appear to come close to resembling a structure that looked like a wide op en conformation. The ig7 simulation be comes the closest to resembling a structure that could be a wideopen conf ormation. The f luctuations of this particular simulation become as low as 4 angstroms during certain points of the dynamics The lack of the dynamics favoring the more the wide open conformation could be do to either not enough sampling or the wide open co nformation is just not prevalent structure of the flap dynamics as a whole. The large conformation of the flaps may appear on a time scale that is beyond our capabilities to simulate.

PAGE 34

34 Figure 3 9. Illustrates the Root Mean Squared Deviation of the C versus time of ten different simulations of Subtype B (PDB ID 1OHR) closed conformation. The first frame of each simulation was used as the reference.

PAGE 35

35 Figure 310. Root Mean Squar ed Deviation of the flap residues 43 58 C and 43 58 C of each monomer versus time for the ten diff eren t simulations of Subtype B ( 1OHR) closed conformation. The red was v ersus the closed conformation. The green was versus the semi open conforma tion The blue was versus the (fully) wide open conformati on.

PAGE 36

36 Fluctuations are seen as low as 1 angstrom and as high as 4.5 angstroms in Figure 3 9, in which the starting coordinates were 1OHR Simulations ig4, ig7 and ig10 show the highest fluctuations. Furthe rmore, the fluctuations in the ig10 simulation quickly rise to 4.5, where it remains throughout the simulation. This can be explained because in Figure 3 10 we observe that the ig10 simulation first favors a closed conformation but quickly reverts to favor ing a semi open conformation. The ig7 simulation abruptly rises to 4.5 angstroms but then decreases to 3 angstroms. As seen in previous sections the flaps favor a conformation other than the semi open conforma tion. In contrast, in the ig5 simulation we see that the closed conformation is preferred. The fact that the closed conform ation is dominant in one simulation could be attributed to the flaps beginning the simulation from a closed structure. In the ig1 simulation, it is observed that the closed conf ormation is preferable at the beginning but the deviations only get as close as 2 angstroms and that is only for a brief moment. The ig1 simulation demonstrates another example of the flaps in a conformation that is neither closed or semiopen. The flaps could either be tucked or curled The wide open conformation is not the dominant conformation in any of the simulations. The simulations of ig3, ig7 and ig10 do however become as close as 3 angstroms to the w ide open conformations. When comparing all the subtype B simulations similar trends can be seen in all of them. We observe that the semi open conformation is the pref erred conformation of all the simulations. On the other hand, simulations 1OHR and 2BPX do show more instances in which the dynamics favor the closed conformation. Further investigation is needed in order to explain why this is the case. Performing an energy decomposition analysis might give insight to what interactions are different between 1HHP, 2PBX and 1OHR.

PAGE 37

37 Figure 3 11. Illustrates the Root Mean Squared Deviation of the C versus time of ten di fferent simulations of Subtype C (PDB ID 2R8N) wide open conformation. The first frame of each simulation was used as the ref erence.

PAGE 38

38 Figure 3 12. Root Mean Squared Deviation of the flap residues 43 58 C and 43 58 C of each monomer versus time for the ten di fferent simulations of Subtype C ( 2R8N) wide open conformation. The red was versus the closed conforma tion and the crystal structure The green was versus the semi open conforma tion The blue was versus the (fully) wide open conformation.

PAGE 39

39 In Figure 3 11, where the initial coordinates were 2R8N, we observe deviations primarily between 1 and 4 angstr oms. In all of the simulations there are no sudden rises or declines in fluctuations except in the simulation ig3. This sharp rise is due m ainly in part that the flaps switch from semiopen to a close d conformation. From Figure 312, it is clear that the p referred structure is one in which the flaps favor the semi open conformation. In many of the simulations we see that the dynamics get as close as 1 angstrom to the semi open conformation. This strong preference for the semi open conformation could be poss ibly linked to the fact that the initial coordinates of the flaps were in a conformation, which is considered to be wide open. Nevertheless, only the dynamics of the ig2 simulation in Figure 3 12 favor a conformation other than semi open. In this special case the trajectory never deviates more than 2 angstroms from the closed structure except when the simulation first begins in which the deviation is at 4 angstroms. The ig9 simulation shows a very unique trend. There are points in the ig9 simulation where the fluctuations when compared to the semi open structure suddenly increase. Usually w hen this occurs, the fluctuation when c ompared to the closed structure decreases; however, this trend is not seen. At that particular instance one could assume that the dynamics favor either tucked or curled conformation. For almost all of the simulations with a few exceptions the fluctuations remain between 6 8 angstroms when compared against the wide open structure In particular, during the ig7 simulation we observe that the flaps come within 2 angstroms of the wide open conformation. It could be proposed that the flaps exhibit semi open conformation that favor s more of a wide open conformation. As se en in the subtype B simulations, the dynamics of the structure that did not begin the simulation closed favors the wide open conformation a lot more when compared to the two simulations in which the starting structures were closed

PAGE 40

40 Figure 3 13. Illustrates the Root Mean Squared Deviation of the C versus time of ten different simulation s of Subtype C (PDB ID 2R5P ) closed conformation. The first frame of each simulation was used as the reference.

PAGE 41

41 Figure 3 14. Root Mean Squared Deviation of the flap residues 43 58 C and 43 58 C of each monomer versus time for the ten diff erent simulations of Subtype C (2R5P) The red was versus the clo sed conformation. The green was versus t he semi open conformation. The blue was versus the (fully) wide open conformation.

PAGE 42

42 The range of fluctuations on average is between 14 angstroms for each of the ten simulations in Figure 3 13 The initial starting coordinates were gathered from 2R5P The highest fluctuations are seen in the ig3 simulation when deviations become as high as 5 angstrom s around 20,000 ps. The rapid fluctuation can be attributed to the fact that at that same time frame we s ee that the flaps revert from favoring a close conformation to that of a semi open confor mation. In addition, the flaps suddenly adapt a conformation, w hich deviates more than 4 angstroms from the closed conformation. It is evident from the ten simulations in Figu re 3 14 t hat flaps favor a conformation that is semi open. The ig2, ig4, ig9, and ig10 simulations first initially favor tucked or curled conformation but then it is seen that the semi open conformation becomes the dominant form. The fluctuations from the semi open structure become as low as 1 angstrom in certain simulations. Even though the dynamics began from a conformation which was closed, it still favored the semi open conformation, which was not the case for the structures that were initially closed for subtype B. The closed tucked and curled conformations are not the predominant form of the flaps in any of the dynamics, which is not the c ase in the simulations of 2R8N. In the ig2 and ig10 simulation we do see that the both the closed, semi open, and wide open conformation are not favored in the beginning. This suggests as stated earlier that flaps are in a tucked or curl ed position. The w ide open conformat ion is not the dominant form in any of the simulations. We do however see points of the simulation in which the deviations become as small as 3 angstroms versus the wide open structure as seen in the ig8 simulation in Figure 314 As stated earlier the lack of the dynamics favoring the wide open conformation could be do sampling or either the reference structure we chose to represent the wide open conformation.

PAGE 43

43 Figure 315. Illustrates the Root Mean Squared D eviation of the C versus time of ten diff erent simulations of Subtype C (PDB ID code 2R5Q) closed conformation. The first frame of each simulation was used as the reference.

PAGE 44

44 Figure 3 16. Root Mean Squared Deviation of the flap residues 43 58 C and 43 58 C of each monomer versus time for the ten diff erent simulations of Subtype C ( 2R5Q ) closed conformation. The red was versus the closed conforma tion The green was versus the semi open conforma tion The blue was versus the (fully) wide open conformation.

PAGE 45

45 The initial starting coordinates were gathered from 2R5Q for t he results shown in Figures 315 and 316. Only small de viations are seen in Figure 3 15 with a low of 1 angstrom and a high of 3.5 angstroms. No sudden or abrupt rises in the fluctuations are observed in any of the simulation s in Figure 315 As seen in the other two simulations of subtype C, (2R8N, 2R5P) the main orientation of the flaps appears to be semi open. In addition, the fluctuations become as close as 1 angstrom to the semiopen conformation as seen in the ig1 and ig3 simulations. Unlike the simulations 2R5P there are a few simulations in which the semiopen conformation is not the preferred conformation. The ig4, ig5 and ig7 simulations are examples in which a conformation other than semi open is dominant. In the ig4 and ig7 simulations the dominant conformation could either be curled or tucked because none of the fluctuations versus the closed, semi open, and wide open become lower than 3 angstroms. Fur ther examples of the tucked or curled can be seen in the ig1 simulation In the particular case of ig1, although the semi open conformation is the predominate form around 10,000 ps we see that the dynamics do not look like any of the three reference structures. The wide open conformation as seen in the previous results is not the dominant form in any of the simulations shown in Figure 316. We do observe fluctuations in the flaps that become as low as 3 angstroms as seen in the ig3, ig6 and ig9 simulations One trend that is seen throughout is that even when the dynamics favor the wide open structure it is only for a brief instance and further investigation is needed to explain this. One hypothesis is that it is more energetically favorable for the flaps t o be in semi open conformation rather the wide open conformation. All three simulations of subtypes C favor the semi open conformation as a whole. There are fewer instances in the simulation of subtype C where the dynamics favor the c losed conformation when compared to the simulations of Subtype B.

PAGE 46

46 Figure 3 17. Illustrates the Root Mean Squared Deviation of the C versus time of ten diff erent simulations of Subtype F (PDB ID code 2P3C) closed conformation. The f irst frame of each simulation was used as the reference.

PAGE 47

47 Figure 3 18. Root Mean Squared Deviation of the flap residues 43 58 C and 43 58 C of each monomer of S ubtype F 23PC closed conformation. The red was versus the closed conforma tion The green was versus the semi open conforma tion The blue was versus the (fully) wide open conformation

PAGE 48

48 Figures 3 17 and 318 are the results in which the initial coordinates are gathered from 23PC. Generally m ost of the simulations in Figure 3 17 fluctuate between 1 and 3.5 angstroms. However in the ig5 simulation, a peak is observed at around 5 angstroms, which is due to the flaps abruptly switching from a closed to a semi open conformation. As seen with the prev ious simulations, the predominant form of the flaps is not the semi open conformation. Only in the ig3 and ig4 simulations do we see that the dynamics greatly favor the semi open conformation. It is the closed tucked or curled structure, which is favor ed by most of the simulations in Figure 3 18. An example of the dynamics giving rise to either a tucked or curled structure can b e seen in the ig8 simulation. Around 3,000 ps in the ig8 simulation, we see that the dynam ics do not favor either a closed, sem i open, or wide open structure. The wide open conformation is not the dominant structure in any of the simulations. However, some of the simulations do show fluctuations as low as 4 angstroms, which is evident in simulations ig2 and ig9. The flaps of subty pe F do appear to be the most rigid when compared to the other subt y pes. 3.3.2 Comparison of the T hree I nitial S tructures in Subtypes B and Subtypes C In this next section we will compare the three different structures of subtype B and three different structures of subtype C. As mentioned earlier, the initial coordinates for two of the three structures of subtypes B and C were gathered from a closed conformation with an inhibitor bound. We hypothesize that regardless of the initial starting structure t he dynamics more or less should look the same because all three have the same amino acid sequence. Our hypothesis rests on the fact that we have sampled enough phase space as well. In order to address the issue as stated in the methods section of this chapter each structure was simulated using ten different initial velocities. If we have not sampled enough phase space then surely the simulations, which began closed should favor each other while the simulation that began semi/wide open should be different.

PAGE 49

49 Figure 319. Histogram of the distance between ILE50 and ILE50. Comparison of the Subtype B simulations Figure 3 20. Histogram of the distance between VAL82 and VAL82. Comparison of the Subtype B simulations.

PAGE 50

50 Figure 3 21. Histogram of the distance between LYS55 and LYS55. Comparison of the three B subtype simulations. Figure 3 22. Histogram of the distance between the ILE50 and THR80 and vice versa. Comparison of the three subtype B simulations

PAGE 51

51 Figure 3 23. Histogram of the dista nce between ILE50 and Asp25 of each monomer. Comparison of the three subtype B simulations. We will first begin with comparing the three simulations of Subtype B. The first distance taken into consideration was the distance between residues ILE50 and ILE50. This distance gives a good indication of the flap tip se paration. As seen in Figure 319, all three simulations have three peaks. The peaks are found at 5, 9 and 13 angstroms. Figure 3 20 is a measure of the distances between the residues VAL82 and VA L82, which are located in the active site. The 2BPX and 1OHR simulations exhibit peaks at around 20 angstroms. The 1HHP simulation, however, has a peak that is displaced from t he ot her two simulations. The peak for the 1HHP simulation is seen at 23 angstr oms. The difference between the two simulations, which started closed and one simulati on that initially started semiopen, is a lo t more pronounced in Figure 320 than in Figure 3 19. The distance between the LYS55 an d LYS55 is shown in Figure 321. As seen in the other figures the 2BPX and 1OHR simulations look the same. The 1HHP and the 2BPX simulation differ the most while the 1OHR simulation shares charac teristics of both

PAGE 52

52 simulations. Although a ll three simulations exhibit peaks at 26 angstroms the peak for the 1HHP simulation is far more pronounced. Figure 322 is a measure between ILE50 of one monomer and the THR80 of the other monomer When the flaps invert the distances these residues become very close. Figure 3 22 illustrates the first time in which the distribution of distances of 2BPX and the 1OHR simulations differ. Next the distance between the ILE50 and Asp25 of each monomer was measured as shown in Figure 323. ILE50 is located in the flaps and Asp25 is located at the base of the act ive site. It is seen that the distance profiles of all three simulations look very similar, which has not been the case in previous figures. From the previous figures it is suggested that the dynamics of the 2BPX an d the 1OHR look the same. The dynamics of the 1HHP simulations do not look the same. Figure 3 24. Histogram of the distance between ILE50 and ILE50. Comparison of the three Subtype C simulations.

PAGE 53

53 Figure 3 25. Histogram of the distance between VAL82 and VAL82. Comparison of the three su btype C simulations. Figure 3 26. Histogram of the distance between LYS55 and LYS55. Comparison of the three subtype C simulations.

PAGE 54

54 Figure 3 27. Histogram of the distance between ILE50 and THR80 and ILE50 and THR80. Comparison of the three subtype C simulations. Figure 3 28. Histogram of the distance between ASP25 and ILE50 and ASP25 and ILE50. Comparison of the three subtype C simulations.

PAGE 55

55 Figure 3 24 is a histogram of the distance between ILE50 and ILE50. The simulations look very similar except that the peak at 13 angstroms is more prominent in the 2R5P and 2R5Q simulations than in the 2R8N simulations. As seen before with the subtype B simulations the two structures, which began initially clos ed look the same. In Figure 3 25, the distance between VAL82 and VAL82 was measured. The distance profiles of all three simulations favor each other As seen when the same distance was measured for the subty pe B simulations, 2R8N max peak is slightly displaced from 2R5P and 2R5Q pea ks. The LYS55 and the LYS55 distances profiles exhibit very similar trends as seen in Figure 3 26. The 2R5Q and 2R5P dynamics exhibit peaks at 17 angstroms, which is not exhibited by the 2R8N dynamics. Figure 3 27 shows a histogram of the ILE50 and THR80 distances of each monomer. Other than the strong peak at 5 angstroms for 2R5Q, all three simulations look almost the same, which was not the case for the three subtype B simula tion s. The last plot Figure 3 28 show the distances between ILE50 and Asp25. The plots of all three look very similar with slight differences. The peaks at 13 angstroms are more prominent in the 2R5P and 2R5Q. 2R5Q does exhibit a slight peak at 26 angstroms, w hich is not prevalent in 2R8N and 2R5P. The dynamics of all three simulations look a lot closer than the three s imulations of subtype B. The reason why there is better agreement for the subtype C simulations of our original hypothesis that the dynamics sh ould look the same no matter the initial coordinates needs f urther investigation. 3.3.3 Comparison between the D ifferent S ubtypes In this section a comparison will be made between each of the four different subtypes. The nomenclature will be as follow s : subtype A is 3IXO, Subtype B is 1OHR, Subtype C is 2R5Q, and Subtype F is 2P3C. The reason why 1OHR and 2R5Q were chosen as representative structures of each of their subtypes was because they begin from initially closed conformations As men tioned in s ection 3.2, although subtype A was crystallized in its apo form the flaps w ere

PAGE 56

56 found to be in a closed conformation and subtype F was crystallized with the inhibitor bound TL 3 with the flaps in a closed conformation. Figure 3 29. The atomic fluctuatio ns of the C Comparison of subtypes A, B, C, F The reference structures used t o produce Figure 3 29 were determined by calculating the average structure for each of the simulations using the ptraj module of AMBER. In Figure 329 all of the subtypes exhibit high fluctuations between residues 43 through 58. These particular residues are foun d in the flaps, so the large fluctuations are due to the fact that the flaps sample many different conformations as seen in previous figures. Of the flap residues, residues 4852 move the most because this area is Gly rich46 62. In general most of the residues fluctuate 1 or 2 angstroms from thei r average structure. The residue 99, which is a PRO fluctuates as high as 5 angstrom s in subtype B and further investigation is needed to explain this phenomena. One explanation could be that PRO is located at the N ter rminus which is the same for all of the other sequences is unable to form a stable interaction with any of the surrounding residues thus

PAGE 57

57 preventing it from bei ng so floppy. However, in subtypes A and C there is a H69K mutation and because of the longer sidechain it can form a stable salt bridge with the C terminal carboxy group of P HE58. The stable salt bridge adds rigidity to the P HE which prevents it from moving so much. Figure 3 30. Histogram of the distance between ILE50 and ILE 50. Compa rison of the different subtypes In Figure 3 30 we compare the flap tip separation for each of the subtypes. Three of the four subtypes exhibit three distinct peaks. Subtype A only exhibits two peaks. All the subtypes have peaks that are around 7 angs troms. Subtype A and C appear the most at this particular distance. The second peak is around 8 angstroms for all of the subtypes except for subtype F. Subtype F is commonly seen throughout the dynamics to be at 10 angstroms. All but subtype A show a significant peak at more or less 13 an gstro ms. It can be suggested that the flap tip separation is on average smaller for subtype A then r est of the subtypes. Figure 330 strengthens the argument that wide open conformation is not a large portion of the dynamics sampled. The

PAGE 58

58 distances of whi ch we g enerally see the flap tip separation spans from 5 to 15 angstroms. Whether or not the ILE50 and ILE50 has any direct correlation to drug resistance is still uncertain. Although, one could propose that the distance corresponds to the ease at which a ligand could enter the active site and potentially bind. Figure 3 31. Histogram of the distance VAL82 and VAL82. Comparison of the different subtypes. Figure 3 31 gives some insight on the average size of the active site. Mutation s are commonly seen in these act ive site re sidues, which result in the loss of hydrophobic interactions with the ligand63 64 65. Unlike the ILE50 ILE50 distance, this distance does correspond to drug resistance. Subtype A exhibits the largest separation between these residues with a peak at 25 angstroms. The differences between subtypes B, C, and F are less pronounced. However, the distance between the pair of residues is slightly larger for subtype C. The implications of the significance of this difference between subtype A and the other subtypes need further investigation.

PAGE 59

59 Figure 3 32. Histogram of the distance between LYS55 and LYS55. Comparison between the different subtypes The LYS55 LYS55 distance gives further insight into possible orientation of the flaps. The distance between the two residues seem s to be the greatest for subtypes A, and C. They both exhibit strong peaks at around 27 angstr oms. In the case of subtype F, the distance between the pair of residue s appears to be smallest. It has the highest probability of being at 18 angstroms. Though the peaks at which we commonly see these distances do not agree with those produce d by Kear et al. they do however match the trends60. The reason why the exact distances of the peaks do not coincide can be linked to a myriad of reasons, for example, different sequence simulated, solvent modeled implicitly, absence of spinlabels etc. The experimental results of the EPR experiments have been able to be reproduced using computational methods66. The measurement of this distance has not been directly correlated to drug resistance but does however offer insight into flap orientation66. In figure 336 we show how the LYS55 LYS55 gives a better indication of the flaps when compared to ILE50 ILE50 dista nce.

PAGE 60

60 Figure 3 33. Histogram of the difference between ILE50 and THR80 ILE50 and THR80. Comparison of different subtypes. This distance as of yet has not been correlated to drug resistance but does however suggest possible conformation of the flaps. As seen during the dynamics when the flaps invert the distance between ILE 50 THR80 becomes small while the distance between ILE50 THR 80 becomes large, thus making i nversion of the flaps possible. T his is the reason why the spectrum at which we see thi s distance is so broad. One interesting trend obs erved in Figure 3 33 is that both sets of distances for each subtypes are more or less the same except for subtype F. One of ILE50 THR80 distances for subtype F is seen to be closer more frequently than the other and further investigation is needed in order to explain this. In the example of subtype F when the one flap s is interacting str ongly the 80s loop of the opposite monomer that flap actually lies over the active site thus preventing access to it. The strong 5080 interaction is stabilized by hydrogen bonding. Subtype A does have a mutation in the 80s loop that might e xplain why this interaction is not as prevalent in its dynamics. Subtypes B and C have the same sequence and it not clear as

PAGE 61

6 1 to why th is same strong interaction is not observed. This conformation could have some impact on ease at which such things as protease inhibitors can bind but further experiments need to be performed in order to confirm this. Another explanation could be that we modeled the solvation implicitly instead of explicitly and that this strong interaction seen between the flap tips and the 80s loop of the other monomer is due to the absence of water. Figure 3 34. Histo gram of the distance between ASP 25 and ILE50 of each monomer. Comparison of the different subtypes. Similar to the VAL82 VAL82 distance the ASP25ILE50 distance does provide information on the size of the active site and has been linked to drug resistance. Subtype s A and C have fairly large peaks whic h are seen at 25 angstroms, and it coincides with them both having a larger VAL82 VAL82 distance. There is a small peak at 10 angstroms in subtype B that is not prevalent in any of the other subtypes. Subtypes B and F exhibit fairly significant peaks at 15 angs troms. The distances of the ASP25ILE50 and ASP25 ILE50 of each monomer differ greatly except in the case of subtype of A. This difference is more so evident in subtypes B and

PAGE 62

62 F. The reason for the distances being so different could be due to the s ampling. In case of the subtype F it could be because of the strong interaction that the flap tips of one monomer makes with the opposing 80s loop. Furthermore the ASP 25ILE50 distance does ha ve a large spectrum because it can become as close as 10 angs troms and on the other hand become as large as 30 angstroms from each other. One can assume that the flaps are in closed conformation when this distance is small and in a wide open conformation when this distance becomes large. Clustering analysis needs to be performed in order to confirm this observation Figur e 3 35. Contour plot of the Root Mean Squared Deviation of the closed conformation versus the ILE50 and ILE50 C First row from left to right, Subtype A, Subtype B, and second row subtype C, subtype F.

PAGE 63

63 Figur e 3 36. Contour plot of the Root Mean Squared Deviation of the closed conformation versus the LYS55 and LYS55 C First row from left to right, Subtype A, Subtype B, and second row subtype C, subtype F. The significance of Figures 3 35 and 336 is to validate whether or not one can assume a certain structure at a given distance. The reason the ILE50 ILE50 and the LY S55LYS55 distances were chosen is because these distances indicate flap orientation as stated earlier It i s believed that when these distances are small, the flaps are in a co nformation that resembles a closed conformation and when the distance s are large the flaps resemble an open conformation. In Figure s 3 35 and 336 it is observe d that at one particular di stanc e the RMSD can fluctuate as much as 1 or 3 angstroms so caution should be excercised when using the distances to correlate flap conformation.

PAGE 64

64 3.4 Conclusions From the results above one could propose that subtypes A and C are more open as evident in Figures 3 29, 331, and 333. Furthermore this could explain why certain protease inhibitors are not as effective for inhibiting these protease s but further investigation is needed56 67. Furthermore the fact the subtype C is more open might explain the decrease of the catalytic efficiency of subtype C when compared to subtype B in kinetic studies done by Coman et al56. On the other hand, subtype F appears to be the most rigid. This finding agrees with the hypothesis proposed by Sanches et al. which suggest s that mutations in hinge region result in flap stiffening57. Ther e are some s alt bridge interaction s made in the flap region tha t could be linked or explain flap flexibility. The saltbridge interaction of ARG41Asp 60 is formed more fre quently in subtypes B and C. The LYS41ASP60 interaction is formed but is not that frequent in subtype A however the LYS 41GLU60 salt bridge in subytpe F is rarely seen. Subtype F makes instead the saltbridge LYS43GLU60 which is not seen in any of the ot her subtypes. Subtypes A, B and C make the the salt bridge GLU35Arg57 and in the case of subtype F, ASP35LYS57. These differences in salt bridge may coincide as to why the flaps are seen to invert more for subytpes B and C. As previously explai ned in Chapter 2, one must be cautious because the GB model does over stabilize saltbridge interactions. Genomi et al. identified residues 1120 and 11 20 of each monomer as a new potential target for protease inhibition50. In addition, we hypothesize that residues 4043 and 5961 of each monomer could also be proposed as a alternative site for protease inhibition as well The validity of this hypothesis will be tested in future work. The results presented in previous section of this chapter strengthen the hypothesis that nonactive site conformations alter flap dynamics, the size

PAGE 65

65 or shape of the active site63 68. All of these changes can have an impact on the affinity of the ligand to the protease. Figure 3 37. Potential new region for protease inhibition. The residues highlighted in blue are 4043 and 5961 of each monomer.

PAGE 66

66 LIST OF REFERENCES (1) Weiss, A.; Hollander, H.; Stobo, J. Annu. Rev. Med 1985, 36, 545562. (2) Robertson, D. L.; Anderson, J. P.; Bradac, J. A.; Carr, J. K.; Foley, B.; Funkhouser, R. K.; Gao, F.; Hahn, B. H.; Kalish, M. L.; Kuiken, C.; Learn, G. H.; L eitner, T.; McCutchan, F.; Osmanov, S.; Peeters, M.; Pieniazek, D.; Salminen, M.; Sharp, P. M.; Wolinsky, S.; Korber, B. Science 2000, 288, 55d. (3) Grtler, L. G.; Hauser, P. H.; Eberle, J.; von Brunn, A.; Knapp, S.; Zekeng, L.; Tsague, J. M.; Kaptue, L. J. Virol 1994, 68, 15811585. (4) Simon, F.; Mauclre, P.; Roques, P.; Loussert Ajaka, I.; Mller Trutwin, M. C.; Saragosti, S.; Georges Courbot, M. C.; Barr Sinoussi, F.; BrunVzinet, F. Nat. Med 1998, 4, 10321037. (5) Plantier, J.; Leoz, M.; Dicker son, J. E.; De Oliveira, F.; Cordonnier, F.; Leme, V.; Damond, F.; Robertson, D. L.; Simon, F. Nat. Med 2009, 15, 871872. (6) Penny, M. A.; Thomas, S. J.; Douglas, N. W.; Ranjbar, S.; Holmes, H.; Daniels, R. S. AIDS Res. Hum. Retroviruses 1996, 12, 741747. (7) Archer, J.; Robertson, D. L. AIDS 2007, 21, 16931700. (8) Hemelaar, J.; Gouws, E.; Ghys, P. D.; Osmanov, S. AIDS 2006, 20, W1323. (9) Baeten, J. M.; Chohan, B.; Lavreys, L.; Chohan, V.; McClelland, R. S.; Certain, L.; Mandaliya, K.; Jaoko, W.; Overbaugh, J. J. Infect. Dis 2007, 195, 11771180. (10) Ruben, S.; Perkins, A.; Purcell, R.; Joung, K.; Sia, R.; Burghoff, R.; Haseltine, W. A.; Rosen, C. A. J. Virol 1989, 63, 18. (11) Zapp, M. L.; Green, M. R. Nature 1989, 342, 714716. (12) Lama, J.; Mangasarian, A.; Trono, D. Curr. Biol 1999, 9, 622631. (13) Rogel, M. E.; Wu, L. I.; Emerman, M. J. Virol 1995, 69, 882888. (14) Chan, D. C.; Fass, D.; Berger, J. M.; Kim, P. S. Cell 1997, 89, 263273. (15) Pantophlet, R.; Burton, D. R. Annu. Rev. Immunol 2006, 24, 739769. (16) Coakley, E.; Petropoulos, C. J.; Whitcomb, J. M. Curr. Opin. Infect. Dis 2005, 18, 915. (17) Chan, D. C.; Kim, P. S. Cell 1998, 93, 681684.

PAGE 67

67 (18) Robertson, D. L.; Hahn, B. H.; Sharp, P. M. Journal of Molecular Ev olution 1995, 40, 249259. (19) Pollard, V. W.; Malim, M. H. Annu. Rev. Microbiol. 1998, 52, 491532. (20) Kim, J. B.; Sharp, P. A. Journal of Biological Chemistry 2001, 276, 1231712323. (21) Witte, O. N.; Baltimore, D. J. Virol 1978, 26, 750761. (22) Crawford, S.; Goff, S. P. J. Virol 1985, 53, 899907. (23) Whitford, D. Proteins: structure and function; J. Wiley & Sons, 2005. (24) Kohl, N. E.; Emini, E. A.; Schleif, W. A.; Davis, L. J.; Heimbach, J. C.; Dixon, R. A.; Scolnick, E. M.; Sigal, I. S. Proc. Natl. Acad. Sci. U.S.A 1988, 85, 46864690. (25) Navia, M. A.; Fitzgerald, P. M. D.; McKeever, B. M.; Leu, C.; Heimbach, J. C.; Herber, W. K.; Sigal, I. S.; Darke, P. L.; Springer, J. P. Nature 1989, 337, 615620. (26) Wlodawer, A.; Miller, M.; Jasklski, M.; Sathyanarayana, B. K.; Baldwin, E.; Weber, I. T.; Selk, L. M.; Clawson, L.; Schneider, J.; Kent, S. B. Science 1989, 245, 616 621. (27) Hornak, V.; Okur, A.; Rizzo, R. C.; Simmerling, C. Proc. Natl. Acad. Sci. U.S.A 2006, 103, 915920. (28) Czodrowski, P.; Sotriffer, C. A.; Klebe, G. J Chem Inf Model 2007, 47, 15901598. (29) Meek, T. D.; Rodriguez, E. J.; Angeles, T. S. Meth. Enzymol 1994, 241, 127156. (30) Alder, B. J.; Wainwright, T. E. J. Chem. Phys. 1957, 27, 1208. (31) McCammon, J. A.; Gelin, B. R.; Karplus, M. Nature 1977, 267, 585590. (32) Leach, A. Molecular Modelling: Principles and Applications ; 2nd ed.; Prentice Hall, 2001. (33) Frenkel, D.; Smit, B. Understanding Molecular Simulation, Second Edition: From Algorithms to Applications ; 2nd ed.; Academic Press, 2001 (34) Cramer, C. J. Essentials of Computational Chemistry: Theories and Models ; 2nd ed.; Wiley, 2004. (35) Verlet, L. Phys. Rev. 1967, 159, 98. (36) Hockney, R. Methods Comput. Phys 1970, 9, 136211.

PAGE 68

68 (37) Swope, W.; Andersen, H.; Berens, P.; Wilson, K. The Journal of Chemical Physics 1982, 76, 649, 637. (38) Beeman, D. Journal of Computational Physics 1976, 20, 130139. (39) Hornak, V.; Abel, R.; Okur, A.; Strockbine, B.; Roitberg, A.; Simmerling, C. Proteins 2006, 65, 712725. (40) Onufriev, A.; Case, D. A.; Bashford, D. J Comput Chem 2002, 23, 12971304. (41) Zhou, R. Proteins 2003, 53, 148161. (42) Simmerling, C.; Stroc kbine, B.; Roitberg, A. E. J. Am. Chem. Soc 2002, 124, 1125811259. (43) Ishima, R.; Freedberg, D. I.; Wang, Y. X.; Louis, J. M.; Torchia, D. A. Structure 1999, 7, 10471055. (44) Galiano, L.; Bonora, M.; Fanucci, G. E. Journal of the American Chemical Society 2007, 129, 1100411005. (45) Blackburn, M. E.; Galiano, L.; Veloro, A. M.; Fanucci, G. E. Biophysical Journal 2009, 96, 310a. (46) Scott, W. R.; Schiffer, C. A. Structure 2000, 8, 12591265. (47) Hornak, V.; Okur, A.; Rizzo, R. C.; Simmerling, C J. Am. Chem. Soc 2006, 128, 28122813. (48) Tth, G.; Borics, A. Biochemistry 2006, 45, 66066614. (49) Bonomi, M.; Gervasio, F. L.; Tiana, G.; Provasi, D.; Broglia, R. A.; Parrinello, M. Biophys. J 2007, 93, 28132821. (50) Genoni, A.; Morra, G.; Me rz, K. M.; Colombo, G. Biochemistry 2010, 49 42834295. (51) Batista, P. R.; Wilter, A.; Durham, E. H. A. B.; Pascutti, P. G. Cell Biochem. Biophys 2006, 44, 395404. (52) Spinelli, S.; Liu, Q. Z.; Alzari, P. M.; Hirel, P. H.; Poljak, R. J. Biochimie 1991, 73, 13911396. (53) Kaldor, S. W.; Kalish, V. J.; Davies, J. F.; Shetty, B. V.; Fritz, J. E.; Appelt, K.; Burgess, J. A.; Campanale, K. M.; Chirgadze, N. Y.; Clawson, D. K.; Dressman, B. A.; Hatch, S. D.; Khalil, D. A.; Kosa, M. B.; Lubbehusen, P. P.; Muesing, M. A.; Patick, A. K.; Reich, S. H.; Su, K. S.; Tatlock, J. H. J. Med. Chem 1997, 40, 39793985.

PAGE 69

69 (54) Munshi, S.; Chen, Z.; Li, Y.; Olsen, D. B.; Fraley, M. E.; Hungate, R. W.; Kuo, L. C. Acta Crystallogr. D Biol. Crystallogr 1998, 54, 10531060. (55) Coman, R. M.; Robbins, A. H.; Goodenow, M. M.; Dunn, B. M.; McKenna, R. Acta Crystallogr. D Biol. Crystallogr 2008, D64 754763. (56) Coman, R. M.; Robbins, A. H.; Fernandez, M. A.; Gilliland, C. T.; Sochet, A. A.; Goodenow, M. M.; McKenna, R.; Dunn, B. M. Biochemistry 2008, 47, 731 743. (57) Sanches, M.; Krauchenco, S.; Martins, N. H.; Gustchina, A.; Wlodawer, A.; Polikarpov, I. J. Mol. Biol 2007, 369, 10291040. (58) Robbins, A. H.; Coman, R. M.; Bracho Sanchez, E.; Fernandez, M. A.; Gilliland, C. T.; Li, M.; Agbandje McKenna, M.; Wlodawer, A.; Dunn, B. M.; McKenna, R. Acta Crystallogr D Biol Crystallogr 2010, 66, 233242. (59) Case, D. A.; Cheatham, T. E.; Darden, T.; Gohlke, H.; Luo, R.; Merz, K. M.; Onufriev, A.; Simmerling, C.; Wang, B.; Woods, R. J. J Comput Chem 2005, 26, 16681688. (60) Kear, J. L.; Blackburn, M. E.; Veloro, A. M.; Dunn, B. M.; Fanucci, G. E. Journal of the American Chemical Society 2009, 131, 1465014651. (61) Layten, M.; Hornak, V.; Simmerling, C. J. Am. Chem. Soc 2006, 128, 1336013361. (62 ) Hamelberg, D.; McCammon, J. A. J. Am. Chem. Soc 2005, 127, 1377813779. (63) Clemente, J. C.; Moose, R. E.; Hemrajani, R.; Whitford, L. R. S.; Govindasamy, L.; Reutzel, R.; McKenna, R.; Agbandje McKenna, M.; Goodenow, M. M.; Dunn, B. M. Biochemistry 2004, 43, 1214112151. (64) Rose, R. B.; Craik, C. S.; Stroud, R. M. Biochemistry 1998, 37, 26072621. (65) Logsdon, B. C.; Vickrey, J. F.; Martin, P.; Proteasa, G.; Koepke, J. I.; Terlecky, S. R.; Wawrzak, Z.; Winters, M. A.; Merigan, T. C.; Kovari, L. C. J. Virol 2004, 78, 31233132. (66) Galiano, L.; Ding, F.; Veloro, A. M.; Blackburn, M. E.; Simmerling, C.; Fanucci, G. E. Journal of the American Chemical Society 2009, 131, 430431. (67) Velazquez Campoy, A.; Vega, S.; Freire, E. Biochemistry 2002, 41, 86138619. (68) Clemente, J. C.; Hemrajani, R.; Blum, L. E.; Goodenow, M. M.; Dunn, B. M. Biochemistry 2003, 42, 1502915035.

PAGE 70

70 BIOGRAPH ICAL SKETCH Terry Dwight McGee Jr. was born in Macon, Georgia. He received his bachelors degree from the Florida Agricultural and Mechanical University located in Tallahassee, Flo rida in 2005. The fall of 2008 he entered the U niversity of Florida c hemistry g raduate program to study physical chemistry with an emphasis in c omputationa l c hemistry. Upon entering the graduate program he joined the lab of Dr. Adrian E. Roitberg.