Structure-based drug design: Computational advances

Annual Review of Pharmacology and Toxicology

Volumn 37, Issue , 1997, Pages 71-90

  Marrone, Tami J ^a   Briggs, James M ^a   McCammon, J Andrew ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

computational chemistry; docking; free energy perturbation; structure based drug design

Indexed keywords

COMPUTER; DATA BASE; DRUG DESIGN; DRUG STRUCTURE; MODEL; PRIORITY JOURNAL; REVIEW; STRUCTURE ACTIVITY RELATION; TECHNIQUE;

EID: 0030960230     PISSN: 00664251     EISSN: None     Source Type: Book Series    
DOI: 10.1146/annurev.pharmtox.37.1.71     Document Type: Review

References (104)

1. Statistics obtained from the Web site of the Protein Data Bank: http://www.pdb. bnl.gov
2. Quanta/InsightII/Cerius2. Molecular Simulations Inc., 9685 Scranton Road, San Diego, CA 92121-3752
3. Sybyl. Tripos, Inc., 1699 South Hanley Road, St. Louis, MO 63144-2913
4. CAChe. CAChe Scientific, Inc., P.O. Box 4003, Beaverton, OR 97076
5. MacroModel. Department of Chemistry, Columbia University, New York, NY 10032
6. Grasp. Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032
7. Lam PYS, Jadhav PK, Eyermann CJ, Hodge CN, Ru Y, et al. 1994. Rational design of potent, bioavailable, nonpeptide cyclic ureas as HIV protease inhibitors. Science 263:380-84
8. Sham HL, Zhao C, Stewart KD, Betebenner DA, Lin S, et al. 1996. A novel, picomolar inhibitor of human immunodeficiency virus type 1 protease. J. Med. Chem. 39:392-97
9. Viswanadhan VN, Reddy MR, Wlodawer A, Varney MD, Weinstein JN. 1996. An approach to rapid estimation of relative binding affinities of enzyme inhibitors: application to peptidomimetic inhibitors of the human immunodeficiency virus type 1 protease. J. Med. Chem. 39:705-12
10. Weiner SJ, Kollman PA, Case DA, Singh UC, Ghio C, et al. 1984. A new force field for molecular mechanical simulation of nucleic acids and proteins. J. Am. Chem. Soc. 106:765-84
11. Rosenfeld R, Vajda S, DeLisi C. 1995. Flexible docking and design. Annu. Rev. Biophys. Biomol. Struct. 24:677-700
12. Lybrand TP. 1995. Ligand-protein docking and rational drug design. Curr. Opin. Struct. Biol. 5:224-28
13. Jones G, Willett P. 1995. Docking small-molecule ligands into active sites. Curr. Opin. Biotechnol. 6:652-56
14. Kuntz ID, Meng EC, Shoichet BK. 1994. Structure-based molecular design. Acc. Chem. Res. 27:117-23
15. Schoichet BK, Kuntz ID. 1996. Predicting the structure of protein complexes: a step in the right direction. Chem. & Biol. 3:151-56
16. Goodsell DS, Olsen AJ. 1990. Automated docking of substrates to proteins by simulated annealing. Proteins: Struct. Funct. Genet. 8:195-202
17. Luty BA, Wasserman ZR, Stouten PFW, Hodge CN, Zacharias M, McCammon JA. 1995. A molecular-mechanics/grid method for evaluation of ligand receptor interactions. J. Comput. Chem. 16:454-64
18. Meng EC, Shoichet BK, Kuntz ID. 1992. Automated docking with grid-based energy evaluation. J. Comput. Chem. 13:505-24
19. Goodford PJ. 1985. A computational procedure for determining energetically favorable binding sites on biologically important molecules. J. Med. Chem. 28:849-57
20. Wodak SJ, Janin J. 1978. Computer analysis of protein-protein interaction. J. Mol. Biol. 124:323-42
21. Kuntz ID, Blaney JM, Oatley SJ, Langridge R, Ferrin TE. 1982. A geometric approach to macromolecule-ligand interactions. J. Mol. Biol. 161:269-88
22. Judson RS, Jaeger EP, Treasurywala AM. 1994. A genetic algorithm based method for docking flexible molecules. J. Mol. Struct. Theochem. 308:191-206
23. Jones G, Willett P, Geln RC. 1995. Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J. Mol. Biol. 245:43-53
24. Hart TN, Read RJ. 1992. A multiple-start Monte Carlo docking method. Proteins: Struct. Funct. Genet. 13:206-22
25. Leach AR. 1994. Ligand docking to proteins with discrete side-chain flexibility. J. Mol. Biol. 243:310-26
26. Gulukota K, Vadja S, Delisi C. 1996. Peptide docking using dynamic programming. J. Comput. Chem. 17:418-28
27. DesJarlais RL, Sheridan RP, Dixon JS, Kuntz ID, Venkataraghaven R. 1986. Docking flexible ligands to macromolecular receptors by molecular shape. J. Med. Chem. 29:2149-53
28. Clark KP, Ajay. 1995. Flexible ligand docking without parameter adjustment across four ligand-receptor complexes. J. Comput. Chem. 16:1210-26
29. DesJarlais RL, Seibel GL, Kuntz ID, Furth PS, Alvarez JC, et al. 1990. Structure-based design of nonpeptide inhibitors specific for the human immunodeficiency virus 1 protease. Proc. Natl. Acad. Sci. USA 87:6644-48
30. Ring CS, Sun E, McKerrow JH, Lee GK, Rosenthal PJ, et al. 1993. Structure-based inhibitor design by using protein models for the development of antiparasitic agents. Proc. Natl. Acad. Sci. USA 90:3583-87
31. Schoichet BK, Stroud RM, Santi DV, Kuntz ID, Perry KM. 1993. Structure-based discovery of inhibitors of thymidylate synthase. Science 259:1445-50
32. Boobbyer DNA, Goodford PJ, McWhinnnie PM, Wade RC. 1989. New hydrogenbond potentials for use in determining energetically favorable binding sites on molecules of known structure. J. Med. Chem. 32:1083-94
33. Wade RC, Clark KJ, Goodford PJ. 1993. Further development of hydrogen bond functions for use in determining energetically favorable binding sites on molecules of known structure. 1. ligand probe groups with the ability to form two hydrogen bonds. J. Med. Chem. 36:140-47
34. Wade RC, Goodford PJ. 1993. Further development of hydrogen bond functions for use in determining energetically favorable binding sites on molecules of known structure. 2. ligand probe groups with the ability to form more than two hydrogen bonds. J. Med. Chem. 36:148-56
35. Caflish A, Miranker A, Karplus M. 1993. Multiple copy simultaneous search and construction of ligands in binding sites: application to inhibitors of HIV-1 aspartic proteinase. J. Med. Chem. 36:2142-67
36. Eisen MB, Wiley DC, Karplus M, Hubbard RE. 1994. HOOK: A program for finding novel molecular architectures that satisfy the chemical and steric requirements of a macromolecule binding site. Proteins: Struct. Funct. Genet. 19:199-221
37. Moon JB, Howe WJ. 1991. Computer design of bioactive molecules: a method for receptor-based de novo ligand design. Proteins: Struct. Funct. Genet. 11:314-28
38. Bohm H-J. 1992. The computer program LUDI: a new method for the de novo design of enzyme inhibitors. J. Comput.-Aided Mol. Design 6:61-78
39. Lauri G, Bartlett PA. 1994. CAVEAT: a program to facilitate the design of organic molecules. J. Comput.-Aided Mol. Design 8:51-66
40. Gehlhaar DK, Moerder KE, Zichi D, Sherman CJ, Ogden RC, Freer ST. 1995. De novo design of enzymes inhibitors by Monte Carlo ligand generation. J. Med. Chem. 38:466-72
41. Gillet V, Johnson AP, Mata P, Sike S, Williams P. 1993. SPROUT: a program for structure generation. J. Camput. -Aided Mol. Design 7:127-53
42. Lawrence MC, Davis PC. 1992. CLIX: a search algorithm for finding novel ligands capable of binding proteins of known three-dimensional structure. Proteins: Struct. Funct. Genet. 12:31-41
43. Martin YC. 1992. 3-D database searching in drug design. J. Med. Chem. 35:2145-54
44. Brooks BR, Bruccolari RE, Olafson BD, States DJ, Swaminathan S, Karplus M. 1983. CHARMM: a program for macromolecular energy minimizations and dynamics calculations. J. Comput. Chem. 4:187-217.
45. Weiner SJ, Kollman PA, Case DA, Singh UC, Ghio C, et al. 1984. A new force field for molecular mechanical simulation of nucleic acids. J. Am. Chem. Soc. 106:765-84
46. Weiner SJ, Kollman PA, Nguyen DT, Case DA. 1986. An all atom force field for simulation of proteins and nucleic acids. J. Comput. Chem. 7:230-52
47. Jorgensen WL, Tirado-Rives J. 1988. The OPLS potential functions for proteins. Energy minimizations for crystals of cyclic peptides and crambin. J. Am. Chem. Soc. 110:1657-66
48. Cornell WD, Cieplak P, Bayly CI, Gould IR, Merz KM Jr, et al. 1995. A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J. Am. Chem. Soc. 117:5179-97
49. van Gunsteren WF, Berendsen HJC. 1988. Groningen molecular simulation (GROMOS) library manual. BIOMOS B. V., Nijenborgh 16, 9747 AG Groningen, The Netherlands
50. Mackerell AD, Wiorkiewicz-Kuczera J, Karplus M. 1995. An all-atom empirical energy function for the simulation of nucleic acids. J. Am. Chem. Soc. 117:11946-75
51. Eisenberg D, McLachlan AD. 1986. Solvation energy in protein folding and binding. Nature 319:199-203
52. Wesson L, Eisenberg D. 1992. Atomic solvation parameters applied to molecular dynamics of proteins in solution. Protein Science 1:227-35
53. Ooi T, Oobatake M, Nemethy G, Scheraga HA. 1987. Accessible surface areas as a measure of the thermodynamic parameters of hydration of peptides. Proc. Natl. Acad. Sci. USA 84:3086-90
54. Vila J, Williams RL, Vasquez M, Scheraga HA 1991. Empirical solvation models can be used to differentiate native from near-native conformations of bovine pancreatic-trypsin inhibitors. Proteins: Struct. Funct. Genet. 10:199-218
55. Stouten PFW, Frommel C, Nakamura H, Sander C. 1993. An effective solvation term based on atomic occupancies for use in protein simulations. Mol. Simul. 10:97-120
56. Wasserman ZR, Hodge CN. 1996. Fitting an inhibitor into the active site of thermolysin: a molecular dynamics study. Proteins: Struct. Funct. Genet. 4:227-37
57. Schiffer CA, Caldwell JW, Kollman PA, Stroud RM. 1993. Protein structure prediction with a combined solvation free energy-molecular mechanics force field. Mol. Simul. 10:121-49
58. von Freyburg B, Richmond TJ, Braun W. 1993. Surface area included in energy refinement of proteins. A comparative study on atomic solvation parameters. J. Mol. Biol. 233:275-92
59. Juffer A, Eisenhaber F, Hubbard SJ, Walther D, Argos P. 1995. Comparison of atomic solvation parametric sets: applicability and limitations in protein folding and binding. Protein Science 4:2499-509
60. Gilson MK, McCammon JA, Madura JD. 1995. Molecular dynamics simulations with a continuum electrostatic model of solvent. J. Comput. Chem. 16:1081-95
61. Ewing TJA, Lybrand TP. 1994. A comparison of perturbation methods and Poisson-Boltzmann electrostatics calculations for estimation of relative solvation free energies. J. Phys. Chem. 98:1748-52
62. Shen J, Quiocho FA. 1995. Calculation of binding energy differences for receptor-ligand systems using the Poisson-Boltzmann method. J. Comput. Chem. 16:445-48
63. Shen J, Wendoloski J. 1995. Binding of phosphorus-containing inhibitors to thermolysin studied by the Poisson-Boltzmann method. Protein Science 4:373-81
64. Shen J, Wendoloski J. 1996. Electrostatic binding energy calculation using the finite difference solution to the linearized Poisson-Boltzmann equation: assessment of its accuracy. J. Comput. Chem. 17:350-57
65. Antosiewicz J, McCammon JA, Wlodek S, Gilson MK. 1995. Simulation of charge-mutant acetylcholinesterases. Biochemistry 34:4211-19
66. Antosiewicz J, McCammon JA, Gilson MK. 1994. Prediction of pH-dependent properties of proteins. J. Mol. Biol. 238:415-36
67. Sitkoff D, Sharp KA, Honig B. 1994. Accurate calculation of hydration free energies using macroscopic solvent models. J. Phys. Chem. 98:1978-88
68. Smith KC, Honig B. 1994. Evaluation of the conformational free energies of loops in proteins. Proteins: Struct. Funct. Genet. 18:119-32
69. Yang AS, Honig B. 1995. Free energy determinants of secondary structure formations. 1. Alpha-helices. J. Mol. Biol. 252:351-65
70. Yang AS, Honig B. 1995. Free energy determinants of secondary structure formations. 2. Antiparallel beta-sheets. J. Mol. Biol. 252:366-76
71. Jackson R, Sternberg MJE. 1995. A continuum model for protein-protein interactions: application to the docking problem. J. Mol. Biol. 250:258-75
72. Zacharias M, Luty BA, Davis ME, McCammon JA. 1994. Combined conformational search and finite-difference Poisson-Boltzmann approach for flexible docking: application to an operator mutation in the λ represser-operator complex. J. Mol. Biol. 238:455-65
73. Marrone TJ, Gilson MK, McCammon JA. 1996. Comparison of continuum and explicit models of solvation-potentials of mean force for alanine dipeptide. J. Phys. Chem. 100:1439-41
74. Straatsma TP, McCammon JA. 1992. Computational alchemy. Annu. Rev. Phys. Chem. 43:407-35
75. Tembe BL, McCammon JA. 1984. Ligand-receptor interactions. Comput. Chem. 8:281-83
76. Wong CF, McCammon JA. 1986 Dynamics and design of enzymes and inhibitors. J. Am. Chem. Soc. 108:3830-32
77. Straatsma TP. 1996. Free energy by molecular simulation. In Reviews in Computational Chemistry, ed. KB Lipkowitz, DB Boyd, 9:81-127. New York: VCH Publishers
78. Rao BG, Kim EE, Murcko MA. 1996. Calculation of solvation and binding free energy differences between VX-478 and its analogs by free energy perturbation and amsol methods. J. Comput.-Aided Mol. Design 10:23-30
79. Rami Reddy M, Varney MD, Kalish V, Viswanadham VN, Appelt K. 1994. Calculation of relative differences in the binding free energies of HIV1 protease inhibitors: a thermodynamic cycle perturbation approach. J. Med. Chem. 37:1145-1152
80. Rami Reddy M, Bacquet RJ, Zichi D, Matthews DA, Welsh KM, et al. 1992. Calculation of solvation and binding free energy differences for folate-based inhibitors of the enzyme thymidylate synthase. J. Am. Chem. Soc. 114:10117-22
81. Wlodek ST, Antosiewicz J, McCammon JA, Straatsma TP, Gilson MK, et al. 1996. Binding of tacrine and 6-chlorotacrine by acetylcholinesterase. Biopolymers 38:109-17
82. Marrone TJ, Straatsma TP, Briggs JM, Wilson DK, Quiocho FA, McCammon JA. 1996. Theoretical study of inhibition of adenosine deaminase by 8R-coformycin and 8R-deoxycoformycin. J. Med. Chem. 39:277-84
83. Damewood JR Jr. 1996. Peptide mimetic design with the aid of computational chemistry. In Reviews in Computational Chemistry, ed. KB Lipkowitz, DB Boyd, 9:1-79. New York: VCH Publishers
84. Kollman PA. 1993. Free energy calculations - applications to chemical and biochemical phenomena. Chem. Rev. 93:2395-417
85. Cannon WR, Madura JD, Thummel RP, McCammon JA. 1993. Molecular recognition: effect of rotational isomers on host-guest binding. J. Am. Chem. Soc. 115:879-84
86. McCammon JA. 1994. Free energy and binding selectivity. In Computational Approaches in Supramolecular Chemistry, ed. G. Wipff, 15:515-17. Dordrecht: Kluwer Academic
87. McCammon JA, Harvey S. 1987. Dynamics of Proteins and Nucleic Acids. Cambridge: Cambridge Univ. Press
88. Karplus M, Petsko GA. 1990. Molecular dynamics simulations in biology. Nature 147:631-39
89. Frauenfelder H, Wolynes PG. 1994. Biomolecules: where the physics of complexity and simplicity meet. Physics Today 47:58-64
90. Cummins PL, Gready JE. 1995. The influence of starting coordinates in free energy simulations of ligand binding to dihydrofolate reductase. Mol Simul. 15:155-75
91. Jorgensen WL. 1991. Computational insights on intermolecular interactions and binding in solution. Chemtracts Org. Chem. 4:91-119
92. Chipot C, Maigret B, Pearlman DA, Kollmnan PA. 1996. Molecular dynamics potential of mean force calculations: a study of the toluene-ammonium π-cation interactions. J. Am. Chem. Soc. 118:2998-3005
93. Luty BA, van Gunsteren WF. 1996. Electrostatic interactions using the particle-particle particle-mesh method with non-periodic long-range interactions. J. Phys. Chem. 100:2581
94. Halgren TA. 1995. Potential energy functions. Curr. Opin. Struct. Biol. 5:205-10
95. Clark TW, Hanxleden RV, McCammon JA, Scott LR. 1994. Parallelization using spatial decomposition for molecular dynamics. Scalable High Perform. Comput. Conf., pp. 95-102. IEEE Comput. Soc.
96. Zacharias M, Straatsma TP, McCammon JA. 1994. Separation-shifted scaling, a new scaling method for Lennard-Jones interactions in thermodynamic integration. J. Chem. Phys. 100:9025-31
97. Liu H, Mark AE, van Gunsteren WF. 1996. Estimating the relative free energy a of different molecular states with respect to a single reference state. J. Phys. Chem. 100:9485-94
98. Gibas CJ, Subramaniam S. 1996. Explicit solvent models in protein pKa calculations. Biophys. J. 71:138-47
99. Antosiewicz J, McCammon JA, Gilson MK. 1996. The determinants of pKas in proteins. Biochemistry 35:7819-33
100. Resat H, McCammon JA. 1996. Free energy simulations: correcting for electrostatic cutoffs by use of the Poisson equation. J. Chem. Phys. 104:7645-51
101. Resat H, Mezei M. 1994. Grand canonical Monte Carlo simulations of waters , in crystal hydrates. J. Am. Chem. Soc. 116:7451-52
102. Resat H, Mezei M. 1996. Grand canonical ensemble Monte Carlo simulation of the dCpG/proflavine crystal hydrate. Biophys. J. 71:1179-90
103. Cagin T, Pettitt BM. 1991. Molecular dynamics with a variable number of molecules. Mol Phys. 72:169-75
104. Wade RC, Bohr H, Wolynes PG. 1992. Prediction of water binding sites on proteins by neural networks. J. Am. Chem. Soc. 114:8284-85