Assessing scoring functions for protein-ligand interactions

Journal of Medicinal Chemistry

Volumn 47, Issue 12, 2004, Pages 3032-3047

  Ferrara, Philippe ^a   Gohlke, Holger ^a   Price, Daniel J ^a   Klebe, Gerhard ^b   Brooks III, Charles L ^a  

^a SCRIPPS RESEARCH INSTITUTE   (United States)

^b PHILIPPS UNIVERSITY MARBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LIGAND; PROTEIN; PROTEINASE; TRYPSIN; ZINC;

ACCURACY; ANALYTIC METHOD; ARTICLE; BINDING AFFINITY; BINDING SITE; COMPLEX FORMATION; COMPUTER PROGRAM; CORRELATION ANALYSIS; DIELECTRIC CONSTANT; EVALUATION; FORCE; MODEL; MOLECULAR DYNAMICS; PERFORMANCE; POISSON DISTRIBUTION; PREDICTION; PROTEIN BINDING; PROTEIN CONFORMATION; PROTON TRANSPORT; SCORING SYSTEM; SOLVATION; STANDARD;

BINDING SITES; HIV PROTEASE; HYDROPHOBICITY; LIGANDS; MODELS, MOLECULAR; MOLECULAR CONFORMATION; PROTEINS; PROTONS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SOLVENTS; THERMODYNAMICS; TRYPSIN; ZINC;

EID: 1942471391     PISSN: 00222623     EISSN: None     Source Type: Journal    
DOI: 10.1021/jm030489h     Document Type: Article

References (86)

1. Bleicher, K. H.; Böhm, H. J.; Müller, K.; Alanine, A. I. Hit and lead generation beyond high-throughput screening. Nat. Rev. Drug Discovery 2003, 2, 369-378.
2. Abagyan, R.; Totrov, M.; Kuznetsov, D. ICM - A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation. J. Comput. Chem. 1994, 15, 488-506.
3. Jones, G.; Willett, P.; Glen, R. C. Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J. Mol. Biol. 1995, 245, 43-53.
4. Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol. 1996, 261, 470-489.
5. Ewing, T. J. A.; Kuntz, I. D. Critical evaluation of search algorithms for automated molecular docking and database screening. J. Comput. Chem. 1997, 18, 1175-1189.
6. Morris, G. M.; Goodsell, D. S.; Halliday, R. S.; Huey, R.; Hart, W. E.; Belew, R. K.; Olson, A. J. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J. Comput. Chem. 1998, 19, 1639-1662.
7. Wu, G.; Robertson, D. H.; Brooks, C. L., III; Vieth, M. Detailed analysis of grid-based molecular docking: A case study of CDOCKERA CHARMm-based MD docking algorithm. J. Comput. Chem. 2003, 24, 1549-1562.
8. Luo, R.; Gilson, M. K. Synthetic adenine receptors: Direct calculation of binding affinity and entropy. J. Am. Chem. Soc. 2000, 122, 2934-2937.
9. Mardis, K. L.; Luo, R.; Gilson, M. K. Interpreting trends in the binding of cyclic ureas to HIV-1 protease. J. Mol. Biol. 2001, 309, 507-517.
10. Gohlke, H.; Klebe, G. Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors. Angew. Chem., Int. Ed. 2002, 41, 2644-2676.
11. Bühm, H. J.; Stahl, M. The use of scoring functions in drug discovery applications. In Reviews in Computational Chemistry; Lipkowitz, K. B., Boyd, D. B., Eds.; Wiley-VCH: New York, 2002; Vol. 18, pp 41-87.
12. Majeux, N.; Scarsi, M.; Apostolakis, J.; Ehrhardt, C.; Caisch, A. Exhaustive docking of molecular fragments on protein binding sites with electrostatic solvation. Proteins: Struct., Funct., Genet. 1999, 37, 88-105.
13. Zou, X.; Sun, Y.; Kuntz, I. D. Inclusion of solvation in ligand binding free energy calculations using the generalized-Born model. J. Am. Chem. Soc. 1999, 121, 8033-8043.
14. Böhm, H. J. The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure. J. Comput.-Aided Mol. Des. 1994, 8, 243-256.
15. Böhm, H. J. Prediction of binding constants of protein ligands: A fast method for the prioritization of hits obtained from de novo design or 3d database search programs. J. Comput.-Aided Mol. Des. 1998, 12, 309-323.
16. Sippl, M. J. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins. J. Mol. Biol. 1990, 213, 859-883.
17. DeWitte, R.; Shakhnovich, E. SMoG: de novo design method based on simple, fast, and accurate free energy estimates. 1. Methodology and supporting evidence. J. Am. Chem. Soc. 1996, 118, 11733-11744.
18. Mitchell, J. B. O.; Laskowski, R. A.; Alexander, A.; Thornton, J. M. BLEEP-Potential of mean force describing protein-ligand interactions: I. Generating potential. J. Comput. Chem. 1999, 20, 1165-1176.
19. Muegge, I.; Martin, Y. C. A general and fast scoring function for protein-ligand interactions: A simplified potential approach. J. Med. Chem. 1999, 42, 791-804.
20. Gohlke, H.; Hendlich, M.; Klebe, G. Knowledge-based scoring function to predict protein-ligand interactions. J. Mol. Biol. 2000, 295, 337-356.
21. Charifson, P. S.; Corkery, J. J.; Murcko, M. A.; Walters, W. P. Consensus scoring: A method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins. J. Med. Chem. 1999, 42, 5100-5109.
22. Momany, F. A.; Rone, R. Validation of the general-purpose QUANTA. 3.2/CHARMm force-field. J. Comput. Chem. 1992, 13, 888-900.
23. 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 the binding affinity of ligands in receptor complexes. J. Comput.-Aided Mol. Des. 1997, 11, 425-445.
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. 1997, 267, 727-748.
25. Goodsell, D. S.; Olson, A. J. Automated docking of substrates to proteins by simulated annealing. Proteins: Struct., Funct., Genet. 1990, 8, 195-202.
26. Morris, G. M.; Goodsell, D. S.; Huey, R.; Olson, A. J. Distributed automated docking of exible ligands to proteins: Parallel applications of AutoDock 2.4. J. Comput.-Aided Mol. Des. 1996, 10, 293-304.
27. Roche, O.; Kiyama, R.; Brooks, C. L., III. Ligand-protein database: Linking protein-ligand complex structures to binding data. J. Med. Chem. 2001, 44, 3592-3598.
28. Bissantz, C.; Folkers, G.; Rognan, D. Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. J. Med. Chem. 2000, 43, 4759-4767.
29. Stahl, M.; Rarey, M. Detailed analysis of scoring functions for virtual screening. J. Med. Chem. 2001, 44, 1035-1042.
30. Vieth, M.; Hirst, J.; Kolinski, A.; Brooks, C. L., III. Assessing energy functions for flexible docking. J. Comput. Chem. 1998, 19, 1612-1622.
31. Vieth, M.; Hirst, J.; Dominy, B. N.; Daigler, H.; Brooks, C. L., III. Assessing search strategies for flexible docking. J. Comput. Chem. 1998, 19, 1623-1631.
32. Wang, R.; Lu, Y.; Wang, S. Comparative evaluation of 11 scoring functions for molecular docking. J. Med. Chem. 2003, 46, 2287-2303.
33. Stubbs, M. T.; Reyda, S.; Dullweber, F.; Möller, M.; Klebe, G.; Dorsch, D.; Mederski, W.; Wurziger, H. pH-dependent binding modes observed in trypsin crystals: Lessons for structure-based drug design. ChemBioChem 2002, 3, 246-249.
34. Shoichet, B. K.; Leach, A. R.; Kuntz, I. D. Ligand solvation in molecular docking. Proteins: Struct., Funct., Genet. 1999, 34, 4-16.
35. Wei, B. Q.; Baase, W. A.; Weaver, L. H.; Matthews, B. W.; Shoichet, B. K. A model binding site for testing scoring functions in molecular docking. J. Mol. Biol. 2002, 322, 339-355.
36. Murray, C. W.; Baxter, C. A.; Frenkel, D. The sensitivity of the results of molecular docking to induced fit effects: Application to thrombin, thermolysin and neuraminidase. J. Comput.-Aided Mol. Des. 1999, 13, 547-562.
37. Perez, C.; Ortiz, A. R. Evaluation of docking functions for protein-ligand docking. J. Med. Chem. 2001, 44, 3768-3785.
38. Nissink, J. W. M.; Murray, C.; Hartshorn, M.; Verdonk, M. L.; Cole, J. C.; Taylor, R. A new set for validating predictions of protein-ligand interaction. Proteins: Struct., Funct., Genet. 2002, 49, 457-471.
39. Davis, A. M.; Teague, S. J.; Kleywegt, G. J. Application and limitations of X-ray crystallographic data in structure-based ligand and drug design. Angew. Chem., Int. Ed. 2003, 42, 2718-2736.
40. Fitzgerald, M. M.; Musah, R. A.; McRee, D. E.; Goodin, D. B. A ligand-gated, hinged loop rearrangement opens a channel to a buried artificial protein cavity. Nat. Struct. Biol. 1996, 3, 626-631.
41. Ferguson, D. M.; Radmer, R. J.; Kollman, P. A. Determination of the relative binding free energies inhibitors to HIV-1 protease. J. Med. Chem. 1991, 34, 2654-2659.
42. Harte, W. E., Jr.; Beveridge, D. L. Prediction of the protonation state of the active site aspartyl residues in HIV-1 protease-inhibitor complexes via molecular dynamics simulation. J. Am. Chem. Soc. 1993, 115, 3883-3886.
43. Yamazaki, T.; Nicholson, L. K.; Torchia, D. A.; Wingfield, P.; Stahl, S. J.; Kaufman, J. D.; Eyermann, C. J.; Hodge, C. N.; Lam, P. Y. S.; Ru, Y.; Jadhav, P. K.; Chang, C.-H.; Weber, P. C. NMR and X-ray evidence that the HIV protease catalytic aspartyl groups are protonated in the complex formed by the protease and a non-peptide cyclic urea-based inhibitor. J. Am. Chem. Soc. 1994, 116, 10791-10792.
44. Chen, X.; Tropsha, A. Relative binding free energies of peptide inhibitors of HIV-1 protease: The influence of the active site protonation state. J. Med. Chem. 1995, 38, 42-48.
45. Gomez, J.; Freire, E. Thermodynamic mapping of the inhibitor site of the aspartic protease endothiapepsin. J. Mol. Biol. 1995, 252, 337-350.
46. Smith, R.; Brereton, I. A.; Chai, R. Y.; Kent, S. B. H. Ionization states of the catalytic residues in HIV-1 protease. Nat. Struct. Biol. 1996, 3, 946-950.
47. Tokarski, J. S.; Hopfinger, A. J. Constructing protein models for ligand-receptor binding thermodynamic simulations: An application to a set of peptidometic renin inhibitors. J. Chem. Inf. Comput. Sci. 1997, 37, 779-791.
48. Kulkarni, S. S.; Kulkarni, V. M. Structure based prediction of binding affinity of human immunodeficiency virus-1 protease inhibitors. J. Chem. Inf. Comput. Sci. 1999, 39, 1128-1140.
49. Piana, S.; Sebastiani, D.; Carloni, P.; Parrinello, M. Ab initio molecular dynamics-based assignment of the protonation state of pepstatin A/HIV-1 protease cleavage site. J. Am. Chem. Soc. 2001, 123, 8730-8737.
50. Tawa, G. J.; Topol, I. A.; Burt, S. K.; Erickson, J. W. Calculation of relative binding free energies of peptidic inhibitors to HIV-1 protease and its I84V mutant. J. Am. Chem. Soc. 1998, 120, 8856-8863.
51. Baldwin, E. T.; Bhat, N.; Gulnik, S.; Liu, B.; Topol, I. A.; Kiso, Y.; Mimoto, T.; Mitsuya, H.; Erickson, J. W. Structure of HIV-1 protease with KNI-272, a tight-binding transition-state analog containing allophenylnorstatine. Structure 1995, 3, 581-590.
52. Hoog, S. S.; Zhao, Z.; Winborne, E.; Fisher, S.; Green, D. W.; DesJarlais, R. L.; Newlander, K. A.; Callahan, J. F.; Moore, M. L.; Huffman, W. L.; Abdel-Meguid, S. S. A check on rational drug design: crystal structure of a complex of human immunodeficiency virus type 1 protease with a novel-turn mimetic inhibitor. J. Med. Chem. 1995, 38, 3246-3252.
53. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Zakrzewski, V. G.; Montgomery, J. A., Jr.; Stratmann, R. E.; Burant, J. C.; Dapprich, S.; Millam, J. M.; Daniels, A. D.; Kudin, K. N.; Strain, M. C.; Farkas, O.; Tomasi, J.; Barone, V.; Cossi, M.; Cammi, R.; Mennucci, B.; Pomelli, C.; Adamo, C.; Clifford, S.; Ochterski, J.; Petersson, G. A.; Ayala, P. Y.; Cui, Q.; Morokuma, K.; Malick, D. K.; Rabuck, A. D.; Raghavachari, K.; Foresman, J. B.; Cioslowski, J.; Ortiz, J. V.; Stefanov, B. B.; Liu, G.; Liashenko, A.; Piskorz, P.; Komaromi, I.; Gomperts, R.; Martin, R. L.; Fox, D. J.; Keith, T.; Al-Laham, M. A.; Peng, C. Y.; Nanayakkara, A.; Gonzalez, C.; Challacombe, M.; Gill, P. M. W.; Johnson, B. G.; Chen, W.; Wong, M. W.; Andres, J. L.; Head-Gordon, M.; Replogle, E. S.; Pople, J. A. Gaussian 98; Gaussian, Inc.: Pittsburgh, PA, 1998.
54. Harding, M. M. The geometry of metal-ligand interactions relevant to proteins. Acta Crystallogr. D 1999, 55, 1432-1443.
55. INSIGHT II; Molecular Simulations: San Diego, CA, 2002.
56. Warwicker, J.; Watson, H. C. Calculation of the electric potential in the active site cleft due to α-helix dipoles. J. Mol. Biol. 1982, 157, 671-679.
57. Still, W. C.; Tempczyk, A.; Hawley, R. C.; Hendrickson, T. Semianalytical treatment of solvation for molecular mechanics and dynamics. J. Am. Chem. Soc. 1990, 112, 6127-6129.
58. Brooks, B. R.; Bruccoleri, R. E.; Olafson, B. D.; States, D. J.; Swaminathan, S.; Karplus, M. CHARMM: A program for macromolecular energy, minimization, and dynamics calculations. J. Comput. Chem. 1983, 4, 187-217.
59. Lee, B.; Richards, F. M. The interpretation of protein structures: estimation of static accessibility. J. Mol. Biol. 1971, 55, 379-400.
60. Scarsi, M.; Apostolakis, J.; Caisch, A. Continuum electrostatic energies of macromolecules in aqueous solutions. J. Phys. Chem. A 1997, 101, 8098-8106.
61. Qiu, D.; Shenkin, P. S.; Hollinger, F. P.; Still, W. C. The GB/SA continuum model for solvation. A fast analytical method for the calculation of approximate Born radii. J. Phys. Chem. A 1997, 101, 3005-3014.
62. Dominy, B. N.; BrooksI, C. L., III. Development of a generalized Born model parametrization for proteins and nucleic acids. J. Phys. Chem. B 1999, 103, 3765-3773.
63. Lee, M. S.; Salsbury, F. R.; Brooks, C. L., III. Novel generalized Born models. J. Chem. Phys. 2002, 116, 10606-10614.
64. Lee, M. S.; Feig, M.; Salsbury, F. R.; Brooks, C. L., III. New analytic approximation to the standard molecular volume definition and its application to generalized Born calculations. J. Comput. Chem. 2003, 24, 1348-1356.
65. Weiner, S. J.; Kollman, P. A.; Nguyen, D. T.; Case, D. A. An all atom force field for simulations of proteins and nucleic acids. J. Comput. Chem. 1985, 7, 230-252.
66. Gasteiger, J.; Marsili, M. Iterative partial equalization of orbital electronegativity. A rapid access to atomic charges. Tetrahedron 1980, 36, 3219-3288.
67. SYBYL;, Tripos Associates: St. Louis, MO, 2002.
68. Clark, R. D.; Strizhev, A.; Leonard, J. M.; Blake, J. F.; Matthew, J. B. Consensus scoring for ligand/protein interactions. J. Mol. Graphics Modell. 2002, 20, 281-295.
69. Stouten, P. F. W.; Froemmel, C.; Nakamura, H.; Sander, C. An effective solvation term based on atomic occupancies for use in protein simulations. Mol. Simul. 1993, 10, 97-120.
70. Tsai, C.-J.; Kumar, S.; Ma, B.; Nussinov, R. Folding funnels, binding funnels, and protein function. Protein Sci. 1999, 8, 1181-1190.
71. Verkhivker, G. M.; Bouzida, D.; Gehlhaar, D. K.; Retjo, P. A.; Freer, S. T.; Rose, P. W. Complexity and simplicity of ligand-macromolecule interactions: The energy landscape perspective. Curr. Opin. Struct. Biol. 2002, 12, 197-203.
72. Rankin, K. N.; Sulea, T.; Purisima, E. O. On the transferability of hydration-parametrized continuum electrostatics models to solvated binding calculations. J. Comput. Chem. 2003, 24, 954-962.
73. Hetenyi, C.; van der Spoel, D. Efficient docking of peptides to proteins without prior knowledge of the binding site. Protein Sci. 2002, 11, 1729-1737.
74. Glick, M.; Robinson, D. D.; Grant, G. H.; Richards, W. G. Identification of ligand binding sites on proteins using a multiscale approach. J. Am. Chem. Soc. 2002, 124, 2337-2344.
75. Kangas, E.; Tidor, B. Optimizing electrostatic affinity in ligand-receptor binding: Theory, computation, and ligand properties. J. Chem. Phys. 1998, 109, 7522-7545.
76. Sotriffer, C. A.; Gohlke, H.; Klebe, G. Docking into knowledge-based potential fields: A comparative evaluation of DrugScore. J. Med. Chem. 2002, 45, 1967-1970.
77. Gohlke, H.; Hendlich, M.; Klebe, G. Predicting binding modes, binding affinities and "hot spots" for protein-ligand complexes using a knowledge-based scoring function. Perspect. Drug Discovery Des. 2000, 20, 115-144.
78. Kuntz, I. D.; Chen, K.; Sharp, K. A.; Kollman, P. A. The maximal affinity of ligands. Proc. Natl. Acad. Sci. U.S.A. 1999, 96, 9997-1002.
79. Pan, Y.; Huang, N.; Cho, S.; MacKerell, A. D., Jr. Consideration of molecular weight during compound selection in virtual target-based database screening. J. Chem. Inf. Comput. Sci. 2003, 43, 267-272.
80. Zhang, L. Y.; Gallicchio, E.; Friesner, R. A.; Levy, R. M. Solvents models for protein-ligand binding: Comparison of implicit solvent Poisson and surface generalized Born models with explicit solvent simulations. J. Comput. Chem. 2001, 22, 591-607.
81. Grzybowski, B. A.; Ishchenko, A. V.; Kim, C.-Y.; Topalov, G.; Chapman, R.; Christianson, D. W.; Whitesides, G. M.; Shakhnovich, E. I. Combinatorial computational method gives new picomolar ligands for a known enzyme. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 1270-1273.
82. Ben-Naim, A.; Marcus, Y. Solvation thermodynamics of nonionic solutes. J. Chem. Phys. 1984, 81, 2016-2027.
83. Simonson, T.; Brünger, A. T. Solvation free energies estimated from macroscopic continuum theory: An accuracy assessment. J. Phys. Chem. 1994, 98, 4683-4694.
84. Ashbaugh, H. S.; Kaler, E. W.; Paulaitis, M. E. A "universal" surface area correlation for molecular hydrophobic phenomena. J. Am. Chem. Soc. 1999, 121, 9243-9244.
85. Gallicchio, E.; Kubo, M. M.; Levy, R. M. Enthalpy-entropy and cavity decomposition of alkane hydration free energies: Numerical results and implications for theories of hydrophobic solvation. J. Phys. Chem. B 2000, 104, 6271-6285.
86. Pitera, J. W.; van Gunsteren, W. F. The importance of solute-solvent van der Waals interactions with interior atoms of biopolymers. J. Am. Chem. Soc. 2001, 123, 3163-3164.