Comparative assessment of scoring functions on a diverse test set

Journal of Chemical Information and Modeling

Volumn 49, Issue 4, 2009, Pages 1079-1093

  Cheng, Tiejun ^a   Li, Xun ^a   Li, Yan ^a   Liu, Zhihai ^a   Wang, Renxiao ^a  

^a SHANGHAI INSTITUTE OF ORGANIC CHEMISTRY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; COMPLEXATION; CRYSTAL STRUCTURE; GOLD; LIGANDS; PROTEINS; TESTING;

COMMERCIAL SOFTWARE; COMPARATIVE ASSESSMENT; CONSENSUS SCORING; CORRELATION COEFFICIENT; HIGH RESOLUTION CRYSTAL STRUCTURE; PROTEIN-LIGAND COMPLEXES; ROOT MEAN SQUARE DEVIATIONS; STRUCTURE BASED DRUG DESIGNS;

FUNCTION EVALUATION;

ENZYME INHIBITOR; LIGAND; PROTEIN;

ALGORITHM; ARTICLE; CHEMICAL MODEL; CHEMISTRY; CLASSIFICATION; COMPARATIVE STUDY; COMPUTER PROGRAM; COMPUTER SIMULATION; DRUG DESIGN; DRUG SCREENING; METHODOLOGY; PROTEIN BINDING; PROTEIN CONFORMATION; REPRODUCIBILITY; STRUCTURE ACTIVITY RELATION;

ALGORITHMS; COMPUTER SIMULATION; DRUG DESIGN; DRUG EVALUATION, PRECLINICAL; ENZYME INHIBITORS; LIGANDS; MODELS, CHEMICAL; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEINS; REPRODUCIBILITY OF RESULTS; SOFTWARE; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 66149103553     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci9000053     Document Type: Article

References (88)

1. Jorgensen, W. L. The Many Roles of Computation in Drug Discovery. Science 2004, 303, 1813-1818.
2. Klebe, G. Recent Developments in Structure-Based Drug Design. J. Mol. Med. 2000, 78, 269-281.
3. Gane, P. J.; Dean, P. M. Recent Advances in Structure-Based Rational Drug Design. Curr. Opin. Struct. Biol. 2000, 10, 401-404.
4. Amzel, L. M. Structure-Based Drug Design. Curr. Opin. Biotechnol. 1998, 9, 366-369.
5. Marrone, T. J.; Briggs, J. M.; McCammon, J. A. Structure-Based Drug Design: Computational Advances. Annu. Rev. Pharmacol. Toxicol. 1997, 37, 71-90.
6. Blundell, T. L. Structure-Based Drug Design. Nature (London) 1996, 384, 23-26.
7. Verlinde, C. L.; Hol, W. G. Structure-Based Drug Design: Progress, Results and Challenges. Structure 1994, 2, 577-587.
8. Robertus, J. Structure-Based Drug Design Ten Years On. Nat. Struct. Biol. 1994, 1, 352-354.
9. Colman, P. M. Structure-Based Drug Design. Curr. Opin. Struct. Biol. 1994, 4, 868-874.
10. Warren, G. L.; Andrews, C. W.; Capelli, A. M.; Clarke, B.; LaLonde, J.; Lambert, M. H.; Lindvall, M.; Nevins, N.; Semus, S. F.; Senger, S.; Tedesco, G.; Wall, I. D.; Woolven, J. M.; Peishoff, C. E.; Head, M. S. A Critical Assessment of Docking Programs and Scoring Functions. J. Med. Chem. 2006, 49, 5912-5931.
11. Kellenberger, E.; Rodrigo, J.; Muller, P.; Rognan, D. Comparative Evaluation of Eight Docking Tools for Docking and Virtual Screening Accuracy. Proteins: Struct. Funct. Bioinf. 2004, 57, 225-242.
12. Friesner, R. A.; Banks, J. L.; Murphy, R. B.; Halgren, T. A.; Klicic, J. J.; Mainz, D. T.; Repasky, M. P.; Knoll, E. H.; Shelley, M.; Perry, J. K.; Shaw, D. E.; Francis, P.; Shenkin, P. S. Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy. J. Med. Chem. 2004, 47, 1739-1749.
13. Ewing, T. J. A.; Makino, S.; Skillman, A. G.; Kuntz, I. D. DOCK 4.0: Search Strategies for Automated Molecular Docking of Flexible Molecule Databases. J. Comput.-Aided Mol. Des. 2001, 15, 411-428.
14. 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.
15. Morris, G. M.; Goodsell, D. S.; Huey, R.; Olson, A. J. Distributed Automated Docking of Flexible Ligands to Proteins: Parallel Applications of AutoDock 2.4. J. Comput.-Aided Mol. Des. 1996, 10, 293-304.
16. Goodsell, D. S.; Olson, A. J. Automated Docking of Substrates to Proteins by Simulated Annealing. Proteins: Struct. Funct. Genet. 1990, 8, 195-202.
17. 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.
18. Jain, A. Surflex-Dock 2.1: Robust Performance from Ligand Energetic Modeling, Ring Flexibility, and Knowledge-Based Search. J. Comput.-Aided Mol. Des. 2007, 21, 281-306.
19. Jain, A. N. Surflex: Fully Automatic Flexible Molecular Docking Using a Molecular Similarity-Based Search Engine. J. Med. Chem. 2003, 46, 499-511.
20. Venkatachalam, C. M.; Jiang, X.; Oldfield, T.; Waldman, M. LigandFit: A Novel Method for the Shape-Directed Rapid Docking of Ligands to Protein Active Sites. J. Mol. Graphics Modell. 2003, 21, 289-307.
21. 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.
22. 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.
23. Friesner, R. A.; Murphy, R. B.; Repasky, M. P.; Frye, L. L.; Greenwood, J. R.; Halgren, T. A.; Sanschagrin, P. C.; Mainz, D. T. Extra Precision Glide: Docking and Scoring Incorporating a Model of Hydrophobic Enclosure for Protein-Ligand Complexes. J. Med. Chem. 2006, 49, 6177-6196.
24. McInnes, C. Virtual Screening Strategies in Drug Discovery. Curr. Opin. Chem. Biol. 2007, 11, 494-502.
25. Shoichet, B. K. Virtual Screening of Chemical Libraries. Nature (London) 2004, 432, 862-865.
26. Lyne, P. D. Structure-Based Virtual Screening: An Overview. Drug Discovery Today 2002, 7, 1047-1055.
27. Walters, W. P.; Stahl, M. T.; Murcko, M. A. Virtual Screening - an Overview. Drug Discovery Today 1998, 3, 160-178.
28. Gilson, M. K.; Zhou, H.-X. Calculation of Protein-Ligand Binding Affinities. Annu. Rev. Biophys. Biomol. Struct. 2007, 36, 21-42.
29. 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.
30. Kollman, P. Free Energy Calculations: Applications to Chemical and Biochemical Phenomena. Chem. Rev. 1993, 93, 2395-2417.
31. Jorgensen, W. L. Free Energy Calculations: A Breakthrough for Modeling Organic Chemistry in Solution. Adv. Drug. Delivery Rev. 1989, 22, 184-189.
32. Massova, I.; Kollman, P. Combined Molecular Mechanical and Continuum Solvent Approach (MM-PBSA/GBSA) to Predict Ligand Binding. Perspect. Drug Discovery Des. 2000, 18, 113-135.
33. Carlson, H. A.; Jorgensen, W. L. An Extended Linear Response Method for Determining Free Energies of Hydration. J. Phys. Chem. 1995, 99, 10667-10673.
34. Aqvist, J.; Medina, C.; Samuelsson, J.-E. A New Method for Predicting Binding Affinity in Computer-Aided Drug Design. Protein Ene. 1994, 7, 385-391.
35. Krammer, A.; Kirchhoff, P. D.; Jiang, X.; Venkatachalam, C. M.; Waldman, M. LigScore: A Novel Scoring Function for Predicting Binding Affinities. J. Mol. Graphics Modell. 2005, 23, 395-407.
36. Wang, R.; Lai, L.; Wang, S. Further Development and Validation of Empirical Scoring Functions for Structure-Based Binding Affinity Prediction. J. Comput.-Aided Mol. Des. 2002, 16, 11-26.
37. Wang, R.; Liu, L.; Lai, L.; Tang, Y. SCORE: A New Empirical Method for Estimating the Binding Affinity of a Protein-Ligand Complex. J. Mol. Model. 1998, 4, 379-394.
38. Gehlhaar, D. K.; Bouzida, D.; Rejto, P. A. Rational Drug Design: Novel Methodology and Practical Applications; American Chemical Society: Washington, DC, 1999; pp 292-311.
39. Gehlhaar, D. K.; Verkhivker, G. M.; Rejto, P. A.; Sherman, C. J.; Fogel, D. R.; Fogel, L. J.; Freer, S. T. Molecular Recognition of the Inhibitor AG-1343 by HIV-1 Protease: Conformationally Flexible Docking by Evolutionary Programming. Chem. Biol. 1995, 2, 317-324.
40. Baxter, C. A.; Murray, C. W.; Clark, D. E.; Westhead, D. R.; Eldridge, M. D. Flexible Docking Using Tabu Search and an Empirical Estimate of Binding Affinity. Proteins: Struct. Funct. Genet. 1998, 33, 367-382.
41. 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.
42. Jain, A. N. Scoring Noncovalent Protein-Ligand Interactions: A Continuous Differentiable Function Tuned to Compute Binding Affinities. J. Comput.-Aided Mol. Des. 1996, 10, 427-440.
43. Bohm, 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.
44. Bohm, 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.
45. Mooij, W. T. M.; Verdonk, M. L. General and Targeted Statistical Potentials for Protein-Ligand Interactions. Proteins: Struct. Funct. Bioinf. 2005, 61, 272-287.
46. Velec, H. F. G.; Gohlke, H.; Klebe, G. DrugScoreCSD - Knowledge-Based Scoring Function Derived from Small Molecule Crystal Data with Superior Recognition Rate of Near-Native Ligand Poses and Better Affinity Prediction. J. Med. Chem. 2005, 48, 6296-6303.
47. Gohlke, H.; Hendlich, M.; Klebe, G. Knowledge-Based Scoring Function to Predict Protein-Ligand Interactions. J. Mol. Biol. 2000, 295, 337-356.
48. Muegge, I. PMF Scoring Revisited. J. Med. Chem. 2006, 49, 5895-5902.
49. Muegge, I. Effect of Ligand Volume Correction on PMF Scoring. J. Comput. Chem. 2001, 22, 418-425.
50. Muegge, I. A Knowledge-Based Scoring Function for Protein-Ligand Interactions: Probing the Reference State. Perspect. Drug. Discovery Des. 2000, 20, 99-114.
51. 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.
52. Ferrara, P.; Gohlke, H.; Price, D. J.; Klebe, G.; Brooks, C. L. Assessing Scoring Functions for Protein-Ligand Interactions. J. Med. Chem. 2004, 47, 3032-3047.
53. Marsden, P. M.; Puvanendrampillai, D.; Mitchell, J. B. O.; Glen, R. C. Predicting Protein-Ligand Binding Affinities: A Low Scoring Game. Org. Biomol. Chem. 2004, 2, 3267-3273.
54. Wang, R.; Lu, Y.; Fang, X.; Wang, S. An Extensive Test of 14 Scoring Functions Using the PDBbind Refined Set of 800 Protein-Ligand Complexes. J. Chem. Inf. Comput. Sci. 2004, 44, 2114-2125.
55. Wang, R.; Lu, Y.; Wang, S. Comparative Evaluation of 11 Scoring Functions for Molecular Docking. J. Med. Chem. 2003, 46, 2287-2303.
56. Zhou, Z.; Felts, A. K.; Friesner, R. A.; Levy, R. M. Comparative Performance of Several Flexible Docking Programs and Scoring Functions: Enrichment Studies for a Diverse Set of Pharmaceutically Relevant Targets. J. Chem. Inf. Model. 2007, 47, 1599-1608.
57. Chen, H.; Lyne, P. D.; Giordanetto, F.; Lovell, T.; Li, J. On Evaluating Molecular-Docking Methods for Pose Prediction and Enrichment Factors. J. Chem. Inf. Model. 2006, 46, 401-415.
58. Evers, A.; Klabunde, T. Structure-Based Drug Discovery Using GPCR Homology Modeling: Successful Virtual Screening for Antagonists of the Alphala Adrenergic Receptor. J. Med. Chem. 2005, 48, 1088-1097.
59. Cummings, M. D.; DesJarlais, R. L.; Gibbs, A. C.; Mohan, V.; Jaeger, E. P. Comparison of Automated Docking Programs as Virtual Screening Tools. J. Med. Chem. 2005, 48, 962-976.
60. Kontoyianni, M.; Sokol, G. S.; McClellan, L. M. Evaluation of Library Ranking Efficacy in Virtual Screening. J. Comput. Chem. 2005, 26, 11-22.
61. Kontoyianni, M.; McClellan, L. M.; Sokol, G. S. Evaluation of Docking Performance: Comparative Data on Docking Algorithms. J. Med. Chem. 2004, 47, 558-565.
62. Perola, E.; Walters, W. P.; Charifson, P. S. A Detailed Comparison of Current Docking and Scoring Methods on Systems of Pharmaceutical Relevance. Proteins: Struct. Funct. Bioinf. 2004, 56, 235-249.
63. Hu, X.; Balaz, S.; Shelver, W. H. A Practical Approach to Docking of Zinc Metalloproteinase Inhibitors. J. Mol. Graphics Modell. 2004, 22, 293-307.
64. Xing, L.; Hodgkin, E.; Liu, Q.; Sedlock, D. Evaluation and Application of Multiple Scoring Functions for a Virtual Screening Experiment. J. Comput.-Aided Mol. Des. 2004, 18, 333-344.
65. Bursulaya, B.; Totrov, M.; Abagyan, R.; Brooks, C. Comparative Study of Several Algorithms for Flexible Ligand Docking. J. Comput.-Aided Mol. Des. 2003, 17, 755-763.
66. Stahl, M.; Rarey, M. Detailed Analysis of Scoring Functions for Virtual Screening. J. Med. Chem. 2001, 44, 1035-1042.
67. 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.
68. Irwin, J. J.; Shoichet, B. K. ZINC - a Free Database of Commercially Available Compounds for Virtual Screening. J. Chem. Inf. Model. 2005, 45, 177-182.
69. Huang, N.; Shoichet, B. K.; Irwin, J. J. Benchmarking Sets for Molecular Docking. J. Med. Chem. 2006, 49, 6789-6801.
70. Lee, J.; Seok, C. A Statistical Rescoring Scheme for Protein-Ligand Docking: Consideration of Entropic Effect. Proteins: Struct. Funct. Bioinf. 2008, 70, 1074-1083.
71. Ruvinsky, A. M. Calculations of Protein-Ligand Binding Entropy of Relative and Overall Molecular Motions. J. Comput.-Aided Mol. Des 2007, 21, 361-370.
72. Ruvinsky, A. M. Role of Binding Entropy in the Refinement of Protein-Ligand Docking Predictions: Analysis Based on the Use of 11 Scoring Functions. J. Comput. Chem. 2007, 28, 1364-1372.
73. Huang, S. Y.; Zou, X. An Iterative Knowledge-Based Scoring Function to Predict Protein-Ligand Interactions: II. J. Comput. Chem. 2006, 27, 1876-1882.
74. Zhang, C.; Liu, S.; Zhu, Q.; Zhou, Y. A Knowledge-Based Energy Function for Protein-Ligand, Protein-Protein, and Protein-DNA Complexes. J. Med. Chem. 2005, 48, 2325-2335.
75. Raha, K.; Merz, K. M., Jr. Large-Scale Validation of a Quantum Mechanics Based Scoring Function: Predicting the Binding Affinity and the Binding Mode of a Diverse Set of Protein-Ligand Complexes. J. Med. Chem. 2005, 48, 4558-4575.
76. The Discovery Studio Software, version 2.0; Accelrys Software Inc.: San Diego, CA, 2001.
77. The Sybyl Software, version 7.2; Tripos Inc.: St. Louis, MO, 2006.
78. The Schrodinger Software, version 8.0; Schrodinger, LLC: New York, 2005.
79. Wang, R.; Fang, X.; Lu, Y.; Yang, C. Y.; Wang, S. The PDBbind Database: Methodologies and Updates. J. Med. Chem. 2005, 48, 4111-4119.
80. Wang, R.; Fang, X.; Lu, Y.; Wang, S. The PDBbind Database: Collection of Binding Affinities for Protein-Ligand Complexes with Known Three-Dimensional Structures. J. Med. Chem. 2004, 47, 2977-2980.
81. Berman, H. M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T. N.; Weissig, H.; Shindyalov, I. N.; Bourne, P. E. The Protein Data Bank. Nucleic Acids Res. 2000, 28, 235-242.
82. Zhao, Y.; Cheng, T.; Wang, R. Automatic Perception of Organic Molecules Based on Essential Structural Information. J. Chem. Inf. Model. 2007, 47, 1379-1385.
83. Hartshorn, M. J.; Verdonk, M. L.; Chessari, G.; Brewerton, S. C.; Mooij, W. T. M.; Mortenson, P. N.; Murray, C. W. Diverse, High-Quality Test Set for the Validation of Protein-Ligand Docking Performance. J. Med. Chem. 2007, 50, 726-741.
84. 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.
85. Yang, J. M.; Chen, Y. F.; Shen, T. W.; Kristal, B. S.; Hsu, D. F. Consensus Scoring Criteria for Improving Enrichment in Virtual Screening. J. Chem. Inf. Model. 2005, 45, 1134-1146.
86. 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.
87. Wang, R.; Wang, S. How Does Consensus Scoring Work for Virtual Library Screening? An Idealized Computer Experiment. J. Chem. Inf. Comput. Sci. 2001, 41, 1422-1426.
88. Jansen, J. M.; Martin, E. J. Target-Biased Scoring Approaches and Expert Systems in Structure-Based Virtual Screening. Curr. Opin. Chem. Biol. 2004, 8, 359-364.