A critical assessment of docking programs and scoring functions

Journal of Medicinal Chemistry

Volumn 49, Issue 20, 2006, Pages 5912-5931

  Warren, Gregory L ^a   Andrews, C Webster ^a   Capelli, Anna Maria ^b   Clarke, Brian ^c   LaLonde, Judith ^a,d   Lambert, Millard H ^a   Lindvall, Mika ^c,e   Nevins, Neysa ^a   Semus, Simon F ^a   Senger, Stefan ^c   Tedesco, Giovanna ^b   Wall, Ian D ^c   Woolven, James M ^c   Peishoff, Catherine E ^a   Head, Martha S ^a  

^a GLAXOSMITHKLINE   (United States)

^b GSK   (Italy)

^c GLAXOSMITHKLINE   (United Kingdom)

^d Locus Pharmaceuticals   (United States)

^e NOVARTIS PHARMA AG   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID TRANSFER RNA LIGASE; BLOOD CLOTTING FACTOR 10A; CHECKPOINT KINASE 1; DNA TOPOISOMERASE (ATP HYDROLYSING) B; PEROXISOME PROLIFERATOR ACTIVATED RECEPTOR DELTA; POLYPEPTIDE DEFORMYLASE; PROTEIN; UNCLASSIFIED DRUG; VIRUS ENZYME;

ARTICLE; BINDING AFFINITY; BINDING SITE; COMPUTER PREDICTION; COMPUTER PROGRAM; CONFORMATION; CRYSTALLOGRAPHY; DOCKING PROGRAM; EVALUATION; LIGAND BINDING; MATHEMATICAL COMPUTING; PROTEIN BINDING; REACTION OPTIMIZATION; SCORING TECHNOLOGY; VIRTUAL REALITY;

ALGORITHMS; BINDING SITES; DRUG DESIGN; LIGANDS; MODELS, MOLECULAR; MOLECULAR CONFORMATION; PROTEIN BINDING; PROTEINS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SOFTWARE;

EID: 33749260698     PISSN: 00222623     EISSN: None     Source Type: Journal    
DOI: 10.1021/jm050362n     Document Type: Article

References (57)

1. URL: http://www.rcsb.org/pdb/holdings.html.
2. Knegtel, R. M. A.; Wagener, M. Efficacy and selectivity in flexible database docking. Proteins: Struct., Funct., Genet. 1999, 37, 334-345.
3. Ha, S.; Andreani, R.; Muegge, I. Evaluation of docking/scoring approaches: a comparative study based on MMP3 inhibitors. J. Comput.-Aided Mol. Des. 2000, 14, 435-448.
4. 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.
5. Carlos, P.; Ortiz, A. R. Evaluation of docking functions for proteinligand docking. J. Med. Chem. 2001, 44, 3768-3785.
6. Stahl, M.; Rarey, M. Detailed analysis of scoring functions for virtual screening. J. Med. Chem. 2001, 44, 1035-1042.
7. Doman, T. N.; McGovern, S. L.; Bryan, J.; Witherbee, B. J.; Kasten, T. P.; Kurumbail, R.; Stallings, W. C.; Connolly, D. T.; Shoichet, B. K. Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B. J. Med. Chem. 2002, 45, 2213-2221.
8. Schapira, M.; Raaka, B. M.; Das, S.; Fan, L.; Totrov, M.; Zhou, Z.; Wilson, S. R.; Abagyan, R.; Samuels, H. H. Discovery of diverse thyroid hormone receptor antagonists by high-throughput docking. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 7354-7359.
9. Diller, D. J.; Li, R. Kinases, homology models, and high throughput docking. J. Med. Chem. 2003, 46, 4638-4647.
10. Jenkins, J. L.; Kao, R. Y. T.; Shapiro, R. Virtual screening to enrich hit lists from high-throughput screening: A case study on small-molecule inhibitors of angiogenin. Proteins: Struct., Funct., Genet. 2003, 50, 81-93.
11. Schulz-Gasch, T.; Stahl, M. Binding site characteristics in structure-based virtual screening: Evaluation of current docking tools. J. Mol. Model. 2003, 9, 47-57.
12. Wang, R.; Lu, Y.; Wang, S. Comparative evaluation of 11 scoring functions for molecular docking. J. Med. Chem. 2003, 46, 2287-2303.
13. Ferrara, P.; Gohlke, H.; Price, D. J.; Klebe, G.; Brooks, C. L., III. Assessing scoring functions for protein-ligand interactions. J. Med. Chem. 2004, 47, 3032-3047.
14. 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.
15. Kontoyianni, M.; McClellan, L. M.; Sokol, G. S. Evaluation of docking performance: Comparative data on docking algorithms. J. Med. Chem. 2004, 47, 558-565.
16. Kroemer, R. T.; Vulpetti, A.; McDonald, J. J.; Rohrer, D. C.; Trosset, J.-Y.; Giordanetto, F.; Cotesta, S.; McMartin, C.; Kihlén, M.; Stouten, P. F. W. Assessment of docking poses: Interactions-based accuracy classification (IBAC) versus crystal structure deviations. J. Chem. Inf. Comput. Sci. 2004, 44, 871-881.
17. 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.
18. Kontoyianni, M.; Sokol, G. S.; McClellan, L. M. Evaluation of library ranking efficacy in virtual screening. J. Comput. Chem. 2005, 26, 11-22.
19. Makino, S.; Ewing Todd, J. A.; Kuntz, I. D. DREAM++: Flexible docking program for virtual combinatorial libraries. J. Comput.-Aided Mol. Des. 1999, 13, 513-532.
20. Esposito, E. X.; Baran, K.; Kelly, K.; Madura, J. D. Docking of sulfonamides to carbonic anhydrase II and IV. J. Mol. Graphics Modell. 2000, 18, 283-289.
21. Tao, P.; Lai, L. Protein ligand docking based on empirical method for binding affinity estimation. J. Comput.-Aided Mol. Des. 2001, 15, 429-446.
22. Terp, G. E.; Johansen, B. N.; Christensen, I. T.; Jørgensen, F. S. A new concept for multidimensional selection of ligand conformations (MultiSelect) and multidimensional scoring (MultiScore) of protein-ligand binding affinities. J. Med. Chem. 2001, 44, 2333-2343.
23. 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.
24. 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.
25. Olsen, L.; Pettersson, I.; Hemmingsen, L.; Adolph, H.-W.; Jørgensen, F. S. Docking and scoring of metallo-β-lactamases inhibitors. J. Comput.-Aided Mol. Des. 2004, 18, 287-302.
26. 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.
27. Manning, G.; Whyte, D. B.; Martinez, R.; Hunter, T.; Sudarsanam, S. The protein kinase complement of the human genome. Science 2002, 298, 1912-1934.
28. Zhou, B.-B. S.; Bartek, J. Targeting the checkpoint kinases: chemosensitization versus chemoprotection. Nat. Rev. Cancer 2004, 4, 216-225.
29. Quan, M. L.; Smallheer, J. M. The race to an orally active factor Xa inhibitor: Recent advances. Curr. Opin. Drug Discovery Dev. 2004, 7, 460-469.
30. Gross, C. H.; Parsons, J. D.; Grossman, T. H.; Charifson, P. S.; Bellon, S.; Jernee, J.; Dwyer, M.; Chambers, S. P.; Markland, W.; Botfield, M.; Raybuck, S. A. Active-site residues of Escherichia coli DNA gyrase required in coupling ATP hydrolysis to DNA supercoiling and amino acid substitutions leading to novobiocin resistance. Antibact. Agents Chemotherapy 2003, 47, 1037-1046.
31. Vaughan, M. D.; Sampson, P. B.; Honek, J. F. Methionine in and out of proteins: Targets for drug design. Curr. Med. Chem. 2002, 9, 385-409.
32. Serre, L.; Verdon, G.; Choinowski, T.; Hervouet, N.; Risler, J.-L.; Zelwer, C. How methionyl-tRNA synthetase creates its amino acid recognition pocket upon L-methionine binding. J. Mol. Biol. 2001, 306, 863-876.
33. Wang, M.; Ng, K. K.-S.; Cherney, M. M.; Chan, L.; Yannopoulos, C. G.; Bedard, J.; Morin, N.; Nguyen-Ba, N.; Alaouilsmaili, M. H.; Bethell, R. C.; James, M. N. G. Non-nucleoside analogue inhibitors bind to an allosteric site on HCV NS5B polymerase. Crystal structures and mechanism of inhibition. J. Biol. Chem. 2003, 278, 9489-9495.
34. Kliewer, S. A.; Xu, H. E.; Lambert, M. H.; Willson, T. M. Peroxisome proliferator-activated receptors: From genes to physiology. Rec. Prog. Horm. Res. 2001, 56, 239-263.
35. Holloway, M. K.; et al. A priori prediction of activity for HIV-1 protease inhibitors employing energy minimization in the active site. J. Med. Chem. 1995, 38, 305-317.
36. Word, J. M.; Lovell, S. C.; Richardson, J. S.; Richardson, D. C. Asparagine and glutamine: Using hydrogen atom contacts in the choice of side-chain amide orientation. J. Mol. Biol. 1999, 285, 1735-1747.
37. Kuntz, I. D. Structure-based strategies for drug design and discovery. Science 1992, 257, 1078-1082.
38. Kuntz, I. D.; Meng, E. C.; Shoichet, B. K. Structure-based molecular design. Acc. Chem. Res. 1994, 27, 117-123.
39. Ewing, T. J. A.; Kuntz, I. D. Critical evaluation of search algorithms for automated molecular docking and database screening. J. Comput. Chem. 1997, 1175-1189.
40. Kuntz, I. D.; Blaney, J. M.; Oatley, S. J.; Langridge, R.; Ferrin, T. E. A geometric approach to macromolecule-ligand interactions. J. Mol. Biol. 1982, 269-288.
41. Ewing, T. J.; Makino, S.; Skillman, G. A.; Kuntz, I. D. Dock 4.0. Search strategies for automated molecular docking of flexible molecule databases. J. Comput.-Aided Mol. Des. 2001, 411-428.
42. Ferrin, T. E.; Huang, C. C.; Jarvis, L. E.; Robert, L. The MIDAS display system. J. Mol. Graphics 1988, 13-27.
43. Blaney, J. M.; Dixon, J. S. Docklt, version 1.0; Metaphorics, LLC: Mission Viejo, CA; www.metaphorics.com/products/dockit.html.
44. Gehlhaar, D.; Verkhiver, G.; Reijto, P.; Sherman, C.; Fogel, D.; Fogel, L.; Freer, S. Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming. Chem. Biol. 1995, 2, 317-324.
45. Muegge, I.; Martin, Y. A general and fast scoring function for protein-ligand interactions: A simplified potential approach. J. Med. Chem. 1999, 42, 791-804.
46. 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.
47. Rarey, M.; Kramer, B.; Lengauer, T. The particle concept: Placing discrete water molecules during protein-ligand docking predictions. Proteins: Struct., Funct., Genet. 1999, 34, 17-28.
48. Sybyl, version 6.8; Tripos Inc., St. Louis, MO.
49. 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.-AidedMol. Des. 1994, 8, 243-256.
50. Gohlke, H.; Hendlich, M.; Klebe, G. Knowledge-based scoring function to predict protein-ligand interactions. J. Mol Biol. 2000, 295, 337-356.
51. Balducci, R.; Pearlman, R. S. Confort: A Rational Conformation Analysis Tool. Abstracts of Papers, 217th National Meeting of the American Chemical Society; American Chemical Society: Washington, DC, 1999.
52. 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.
53. 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.
54. CScore as implemented in Sybyl version 6.8; Tripos Inc., St. Louis. MO.
55. 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.
56. Halgren, T. A.; Murphy, R. B.; Friesner, R. A.; Beard, H. S.; Frye, L. L.; Pollard, W. T.; Banks, J. L. Glide: A new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J. Med. Chem. 2004, 1750-1759.
57. Lambert, M. H. Docking Conformationally Flexible Molecules into Protein Binding Sites. In Practical Application of Computer-Aided Drug Design; Charifson, P. S., Ed.; Dekker: New York, 1997.