Predicting structural effects in HIV-1 protease mutant complexes with flexible ligand docking and protein side-chain optimization

Proteins: Structure, Function and Genetics

Volumn 33, Issue 2, 1998, Pages 295-310

  Schaffer, Lana ^a   Verkhivker, Gennady M ^a  

^a AGOURON PHARMACEUTICALS INC   (United States)

Author keywords

Correlated energy landscapes; Dead end elimination; Molecular recognition; Monte Carlo docking; Rotamer library

Indexed keywords

PROTEINASE;

ANALYTIC METHOD; ARTICLE; COMPLEX FORMATION; CRYSTAL STRUCTURE; ENZYME ACTIVE SITE; ENZYME STRUCTURE; HUMAN IMMUNODEFICIENCY VIRUS 1; LIGAND BINDING; MOLECULAR RECOGNITION; NONHUMAN; PRIORITY JOURNAL; PROTEIN CONFORMATION; PROTEIN LIPID INTERACTION; PROTEIN PROTEIN INTERACTION; SYSTEM ANALYSIS;

HIV PROTEASE; HIV PROTEASE INHIBITORS; HIV-1; IMIDAZOLES; LIGANDS; MONTE CARLO METHOD; MUTATION; PROTEIN BINDING; PROTEIN CONFORMATION;

HUMAN IMMUNODEFICIENCY VIRUS; HUMAN IMMUNODEFICIENCY VIRUS 1;

EID: 0031717170     PISSN: 08873585     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1097-0134(19981101)33:2<295::AID-PROT12>3.0.CO;2-F     Document Type: Article

References (81)

1. Kuntz, I.D. Structure-based strategies for drug design and discovery. Science 257:1078-1082, 1992.
2. Cherfils, J., Janin, J. Protein docking algorithms: Simulating molecular recognition. Curr. Opin. Struct. Biol. 3:265-269, 1993.
3. Rosenfeld, R., Vajda, S., DeLisi, C. Flexible docking and design. Annu. Rev. Biophys. Biomol. Struct. 24:677-700, 1995.
4. Jones, G., Willett, P. Docking small-molecule ligands into active sites. Curr. Opin. Biotechnol. 6:652-656, 1995.
5. Gschwend, D.A., Good, A.C., Kuntz, I.D. Molecular docking towards drug discovery. J. Mol. Recognit. 9:175-186, 1996.
6. Jiang, F., Kim, S.H. Soft docking: Matching of molecular surface cubes. J. Mol. Biol. 219:79-102, 1991.
7. Walls, P.H., Sternberg, M.J.E. New algorithm to model protein-protein recognition based on surface complementarity. Applications to antibody-antigen docking. J. Mol. Biol 228:277-297, 1992.
8. Desjarlais, R.L., Dixon, J.S. A shape and chemistry-based docking method and its use in the design of HIV-1 protease inhibitors. J. Comput. Aided Mol. Design 8:231-242, 1994.
9. Vakser I.A., Aflalo, C. Hydrophobic docking: A proposed enhancement to molecular recognition techniques. Proteins 20:320-329, 1994.
10. Jackson, R.M., Sternberg, M.J.E. A continuum model for protein-protein interactions: Application to the docking problem. J. Mol. Biol. 250:258-275, 1995.
11. Fisher, D., Lin, S.L., Wolfson, H.J. Nussinov, R. Ageometry-based suite of molecular docking processes. J. Mol. Biol. 248:459-477, 1995.
12. Wallqvist, A., Covell, D.G. Docking enzyme-inhibitor complexes using a preference-based free energy surface. Proteins 25:403-419, 1996.
13. Weng, Z., Vajda, S., DeLisi, C. Prediction of protein complexes using empirical free energy functions. Protein Sci. 5:614-626, 1996.
14. Shoichet, B.K., Kuntz, I.D. Protein docking and complementarity. J. Mol. Biol. 221:327-346, 1991.
15. Luty, B.A., Wasserman, Z.R., Stouten, P.F.W., C.N. Hodge, Zacharias, M., McCammon, J.A. A molecular mechanics-grid method for evaluation of ligand-receptor interactions. J. Comput. Chem. 16:454-464, 1995.
16. Rarey, M., Kramer, B., Lengauer, T., Klebe, G. A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol. 261:470-489, 1996.
17. Welch, W., Ruppert, J., Jain, A.N. Hammerhead: Fast, fully automated docking of flexible ligands to protein binding sites. Chem. Biol. 3:449-462, 1996.
18. Goodsell, A.S., Olson, A.J. Automated docking of substrates to proteins by simulated annealing. Proteins 8:195-202 1990.
19. Caflish, A., Niederer, P., Anliker, M. Monte Carlo docking of oligopeptides to proteins. Proteins 13:223-230, 1992.
20. Hart, T.N., Read, R.J. A multiple-start Monte Carlo docking method. Proteins 13:206-222, 1992.
21. Apostolakis, J., Pluckthun, A., Caflish, A. Docking small molecules in flexible binding sites. J. Comput Chem 19:21-37, 1998.
22. Oshiro, C.M., Kuntz, I.D., Dixon, J.S. Flexible ligand docking using a genetic algorithm. J. Comput. Aided Mol. Design 9:113-130, 1995.
23. Gehlhaar, D.K., Verkhivker, G.M., Rejto, P.A., et al. Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: Conformationally flexible docking by evolutionary programming. Chem. Biol. 2:317-324, 1995.
24. Jones, G., Willett, P., Glen, R.C., Leach, A.R., Taylor, R. Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol. 267:727-748, 1997.
25. Westhead, D.R., Clark, D.E., Murray, C. W. A comparison of heuristic search algorithms for molecular docking. J. Comput. Aided Mol. Design 11:209-228, 1997.
26. Totrov, M., Abagyan, R. Flexible protein-ligand docking by global energy optimization in internal coordinates. Proteins Suppl. 1:215-220, 1997.
27. Leach, A.R. Ligand docking to proteins with discrete side-chain flexibility. J. Mol. Biol. 235:345-356, 1994.
28. Desmet, J., Wilson, I.A., Joniau, M., De Mayer, M., Lasters, I. Computation of the binding of fully flexible peptides to proteins with flexible side-chains. FASEB J. 11:164-172, 1997.
29. Daniyat, B.I., Mayo, S.L. De novo protein design: Fully automated sequence selection. Science 278:82-87, 1997.
30. Lee, C., Subbiah, S. Prediction of protein side-chain conformation by packing optimization. J. Mol. Biol. 217:373-388 1991.
31. Holm, L., Sander, C. Fast and simple Monte Carlo algorithm for side chain optimization in proteins: application to model building by homology. Proteins 14:213-223, 1992.
32. Tuffery, P., Etchebest, C., Hazout, S., Lavery, R. A critical comparison of search algorithms applied to the optimization of protein side chain conformations. J. Comput Chem 14:790-798, 1993.
33. Eisenmenger, F., Argos, P., Abagyan, R. A method to configure protein side chains from the main-chain trace in homology modeling. J. Mol. Biol. 231:849-860, 1993.
34. Laughton, C.A. Prediction of protein side-chain conformations from local three-dimensional homology relationships. J. Mol. Biol. 235:1088-1097, 1994.
35. Kono, H., Doi, J. Energy minimization method using automata network for sequence and side-chain conformation prediction from given backbone geometry. Proteins 19:244-255, 1994.
36. Koehl, P., Delarue, M. Application of a self-consistent mean field theory to predict protein side-chains conformation and estimate their conformational entropy. J. Mol. Biol. 239:249-275, 1994.
37. Tanimura, R., Kidera, A., Nakamura, H. Determinants of protein side-chain packing. Protein Sci. 3:2358-2365, 1994.
38. Koehl, P., Delarue, M. A self-consistent mean field approach to simultaneous gap closure and side-chain positioning in homology modeling. Nat. Struct. Biol. 2:163-170 1995.
39. Vasquez, M. An evaluation of discrete and continuum search techniques for conformational analysis of side chains in proteins. Biopolymers 36:53-70, 1995.
40. Shenkin, P.S., Farid, H., Fetrow, J.S. Prediction and evaluation of side-chain conformations for protein backbone structures. Proteins 26:323-352, 1996.
41. Sali, A. Modeling mutations and homologous proteins. Curr. Opin. Biotechnol. 6:437-451, 1995.
42. Vasquez, M. Modeling side-chain conformation. Curr. Opin Struct. Biol. 6:217-221, 1996.
43. Lee, C., Levitt, M. Accurate prediction of the stability and activity effects of site-directed mutagenesis on a protein core. Nature 352:448-451, 1991.
44. Lee, C. Predicting protein mutant energetics by self-consistent ensemble optimization. J. Mol. Biol. 236:918-939, 1994.
45. Lee, C. Testing homology modeling on mutant proteins: Predicting structural and thermodynamic effects in the Ala98-Val mutants of T4 lysozyme. Fold. Des. 1:1-14, 1996.
46. Baldwin, E.P., Hajiseyedjavadi, O., Baase, W.A., Matthews, B.W. The role of backbone flexibility in the accommodation of variants that repack the core of T4 lysozyme. Science 262:1715-1718, 1993.
47. Lim, W.A., Hodel, A., Sauer, R., Richards, F.M. The crystal structure of a mutant protein with altered but improved hydrophobic core packing. Proc. Natl. Acad. Sci. USA 91:423-427, 1994.
48. Bryngelson, J.D., Onuchic, J.N., Socci, N.D., Wolynes, PG. Funnels, pathways, and the energy landscape of protein folding: A synthesis. Proteins 21:167-195, 1995.
49. Dill, K.A., Chan, H.S. From Levinthal to pathways to funnels. Nat. Struct. Biol. 4:10-19, 1997.
50. Goldstein, R.F. Efficient rotamer elimination applied to protein side-chains and related spin glasses. Biophys. J 66:1335-1340, 1994.
51. Wlodawer. A.. Erickson, J.W. Structure-based inhibitors of HFV-1 protease. Annu. Rev. Biochem. 62:543-585, 1993.
52. Erikson, J.W. The not-so-great escape. Nat. Struct. Biol. 2:523-529, 1995.
53. Hoog, S.S., Towler, E.M., Zhao, B., Doyle, M.L., Debouck, C., Abdel-Meguid, S.S. Human immunodeficiency virus protease ligand specificity conferred by residues outside of the active site cavity. Biochemistry 35:10279-10286, 1996.
54. Baldwin, E.T., Bhat, T.N., Liu, B., Pattabiraman N., Erickson, J.W. Structural basis of drug resistance for the V82A mutant of HIV-1 proteinase. Nat. Struct. Biol. 2:244-249, 1995.
55. Verkhivker, G., Appell, K., Freer, S.T., Villafranca, J.E. Empirical free energy calculations of ligand-protein crystallographic complexes. I. Knowledge-based ligand-protein interaction potentials applied to the prediction of HIV-1 protease binding affinity. Protein Eng. 8:677-691, 1995.
56. Verkhivker, G. Empirical free energy calculations of human immunodeficiency virus type 1 protease crystallographic complexes. II. Knowledge-based ligand-protein interaction potentials applied to thermodynamic analysis of hydrophobic mutations. In: "Pacific Symposium on Biocomputing-96." Hunter, L., Klein, T.E. (eds.). Singapore: World Scientific, 1996:638-652.
57. Verkhivker, G.M., Rejto, P.A. A mean field model of ligand-protein interactions: Implications for the structural assessment of human immunodeficiency virus type 1 protease complexes and receptor-specific binding. Proc. Natl. Acad. Sci. USA 93:60-64, 1996.
58. Rejto, P.A., Verkhivker, G.M. Unraveling principles of lead discovery: From unfrustrated energy landscapes to novel molecular anchors Proc. Natl. Acad. Sci. USA 93:8945-8950, 1996.
59. Verkhivker, G.M., Rejto, P.A., Gehlhaar, D.K., Freer, S.T. Exploring energy landscapes of molecular recognition by a genetic algorithm: Analysis of the requirements for robust docking of HIV-1 protease and FKBP-12 complexes. Proteins 25:342-353, 1996.
60. Rejto, P.A., Verkhivker, G.M., Gehlhaar, D.K., Freer, S.T. New trends in computational structure prediction of ligand-protein complexes for receptor-based drug design. In: "Computational Simulation of Biomolecular Systems." van Gunsteren, W., Weiner, P., Wilkinson A.J. (eds.). Leiden: ESCOM, 1997:451-465.
61. Verkhivker, G.M., Rejto, P.A. Mean field analysis of FKBP-12 complexes with FK-506 and rapamycin: Implications for a role of crystallographic water molecules in molecular recognition and specificity. Proteins 28:313-324, 1997.
62. Shah, N., Rejto, P.A., Verkhivker, G.M. Structural consensus in ligand-protein docking identifies recognition peptide motifs that bind streptavidin. Proteins 28:421-433, 1997.
63. Mayo, S.L., Olafson, B.D., Goddard, W.A. III. DREIDING: A generic force field for molecular simulation. J. Phys. Chem. 94:8897-8909, 1990.
64. Bouzida, D., Kumar, S., Swendsen, R.H. Efficient Monte Carlo methods for the computer simulation of biological molecules. Phys. Rev. A 45:8894-8901, 1992.
65. Ponder, J.W., Richards, F.M. Tertiary templates for proteins. Use of packing criteria in the enumeration of allowed sequences for different structural classes. J. Mol. Biol. 193:775-791, 1987.
66. Dunbrack, R.L. Jr., Karplus, M. Backbone-dependent rotamer library for proteins. Application to side-chain prediction. J. Mol. Biol. 230:543-574, 1993.
67. Desmet, J., De Maeyer, M., Hazes, B., Lasters, I. The dead-end elimination theorem and its use in protein side-chain positioning. Nature 356:539-542, 1992.
68. Lasters, I., Desmet, J. The fuzzy-end elimination theorem: Correctly implementing the side-chain placement algorithm based on the dead-end elimination theorem. Protein Eng. 6:717-722, 1993.
69. Lasters, I., De Maeyer, M., Desmet, J. Enhanced dead-elimination in the search for the global minimum energy conformation of a collection of protein side chains. Protein Eng. 8:815-822, 1995.
70. Keller, D.A., Shibata, M., Marcus, E., Ornstein, R.L., Rein, R. Finding the global minimum: A fuzzy and elimination implementation. Protein Eng. 8:893-904, 1995.
71. Desmet, J., De Maeyer, M., Lasters, I. The 'dead-end elimination' theorem: A new approach to the side-chain packing problem. In: "The Protein Folding Problem and Tertiary Structure Prediction." Merz, K.M., Jr., Le Grands, S.M. (eds.). Boston: Birkhauser, 1994:307-337.
72. De Maeyer, M., Desmet, J., Lasters, I. All in one: A highly detailed rotamer library improves both accuracy and speed in the modeling of side chains by dead-end elimination. Fold. Des. 2:53-66, 1997.
73. Jorgensen, W.L., Tirado-Rives, J. The OPLS potential functions for proteins. Energy minimizations for crystals of cyclic peptides and crambin. J. Am. Chem. Soc. 110:1657-1666, 1988.
74. Mohamadi, F., Richards, N.G.J., Guida, W.C., et al. Macro-Model - an integrated software system for modeling organic and bioorganic molecules using molecular mechanics. J. Comput. Chem. 11:440-467, 1990.
75. Weiner, S.J., Kollman, P.A., Case, D.A., et al. A new force field for molecular mechanical simulation of nucleic acids and proteins. J. Am. Chem. Soc. 106:765-784, 1984.
76. Still, W.C., Tempczyk, A., Hawley, R.C., Hendrickson, T., Semianalytical treatment of solvation for molecular mechanics and dynamics. J. Am. Chem. Soc. 112:6127-6129, 1990.
77. Hong, L., Treharne, A., Hartsuck, J.A., Foundling, S., Tang, J. Crystal structures of complexes of a peptidic inhibitor with wild-type and two mutant HIV-1 proteases. Biochemistry 35:10627-10633, 1996.
78. Hoog, S.S., Zhao, B., Winborne, E., et al. A check on rotational drug design: Crystal structure of a complex of human immunodeficiency virus type 1 protease with a novel gamma-turn mimetic inhibitor. J. Med. Chem. 38: 3246-3252, 1995.
79. Cummings, M.D., Hart, T.N., Read, R.J. Atomic solvation parameters in the analysis of protein-protein docking results. Protein Sci. 4:2087-2099, 1995.
80. Janin, A.N. Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities. J. Comput. Aided Mol. Design 10:427-440, 1996.
81. Eldridge, M.D., Murray, C.W., Auton, T.R., Paolini, G.V., Mee, R.P. Empirical scoring functions: I. The development of a fast empirical scoring function to estimate binding affinity of ligands in receptor complexes. J. Comput. Aided Mol. Design 11:425-445, 1997.