Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance

Journal of Cheminformatics

Volumn 8, Issue 1, 2016, Pages 1-17

  Chaput, Ludovic ^a,b,c   Martinez Sanz, Juan ^a,b,c   Saettel, Nicolas ^a,c,d   Mouawad, Liliane ^a,b,c  

^a PSL RESEARCH UNIVERSITY   (France)

^b UNIVERSITÉ PARIS SACLAY   (France)

^c Centre de Recherche   (France)

^d UNIVERSITÉ DE CAEN   (France)

Author keywords

BEDROC; Benchmark; Docking; DUD E; FlexX; Glide; Gold; Structure based virtual screening; Surflex

Indexed keywords

EID: 84995505949     PISSN: None     EISSN: 17582946     Source Type: Journal    
DOI: 10.1186/s13321-016-0167-x     Document Type: Article

References (37)

1. Lagarde N, Zagury JF, Montes M (2015) Benchmarking data sets for the evaluation of virtual ligand screening methods: review and perspectives. J Chem Inf Model 55:1297-1307
2. Plewczynski D, Lazniewski M, Augustyniak R, Ginalski K (2011) Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database. J Comput Chem 32:742-755
3. Kellenberger E, Rodrigo J, Muller P, Rognan D (2004) Comparative evaluation of eight docking tools for docking and virtual screening accuracy. Proteins 57:225-242
4. Charifson PS, Corkery JJ, Murcko MA, Walters WP (1999) Consensus scoring: a method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins. J Med Chem 42:5100-5109
5. Warren GL, Andrews CW, Capelli A-M, Clarke B, LaLonde J, Lambert MH, Lindvall M, Nevins N, Semus SF, Senger S et al (2006) A critical assessment of docking programs and scoring functions. J Med Chem 49:5912-5931
6. Keseru GM (2001) A virtual high throughput screen for high affinity cytochrome P450cam substrates. Implications for in silico prediction of drug metabolism. J Comput Aided Mol Des 15:649-657
7. Huang N, Shoichet BK, Irwin JJ (2006) Benchmarking sets for molecular docking. J Med Chem 49:6789-6801
8. Cross JB, Thompson DC, Rai BK, Baber JC, Fan KY, Hu Y, Humblet C (2009) Comparison of several molecular docking programs: pose prediction and virtual screening accuracy. J Chem Inf Model 49:1455-1474
9. Fan H, Irwin JJ, Webb BM, Klebe G, Shoichet BK, Sali A (2009) Molecular docking screens using comparative models of proteins. J Chem Inf Model 49:2512-2527
10. Spitzer R, Jain AN (2012) Surflex-dock: docking benchmarks and real-world application. J Comput Aided Mol Des 26:687-699
11. Liebeschuetz JW, Cole JC, Korb O (2012) Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test. J Comput Aided Mol Des 26:737-748
12. Neves MA, Totrov M, Abagyan R (2012) Docking and scoring with ICM: the benchmarking results and strategies for improvement. J Comput Aided Mol Des 26:675-686
13. Schneider N, Lange G, Hindle S, Klein R, Rarey M (2013) A consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes: methods behind the HYDE scoring function. J Comput Aided Mol Des 27:15-29
14. Hawkins PC, Warren GL, Skillman AG, Nicholls A (2008) How to do an evaluation: pitfalls and traps. J Comput Aided Mol Des 22:179-190
15. Good AC, Oprea TI (2008) Optimization of CAMD techniques 3. Virtual screening enrichment studies: a help or hindrance in tool selection? J Comput Aided Mol Des 22:169-178
16. Irwin JJ (2008) Community benchmarks for virtual screening. J Comput Aided Mol Des 22:193-199
17. Mysinger MM, Carchia M, Irwin JJ, Shoichet BK (2012) Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking. J Med Chem 55:6582-6594
18. Chen YC (2015) Beware of docking! Trends Pharmacol Sci 36:78-95
19. Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727-748
20. Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK et al (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739-1749
21. Jain AN (2003) Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine. J Med Chem 46:499-511
22. Rarey M, Kramer B, Lengauer T, Klebe G (1996) A fast flexible docking method using an incremental construction algorithm. J Mol Biol 261:470-489
23. Truchon JF, Bayly CI (2007) Evaluating virtual screening methods: good and bad metrics for the "early recognition" problem. J Chem Inf Model 47:488-508
24. Chaput L, Martinez-Sanz J, Quiniou E, Rigolet P, Saettel N, Mouawad L (2016) vSDC: a method to improve early recognition in virtual screening when limited experimental resources are available. J Cheminform 8:1
25. Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, Soding J et al (2014) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol 7:539
26. Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727-748
27. Halgren T (2007) New method for fast and accurate binding-site identification and analysis. Chem Biol Drug Des 69:146-148
28. Stahl M, Rarey M (2001) Detailed analysis of scoring functions for virtual screening. J Med Chem 44:1035-1042
29. Schulz-Gasch T, Stahl M (2003) Binding site characteristics in structure-based virtual screening: evaluation of current docking tools. J Mol Model 9:47-57
30. Duan J, Dixon SL, Lowrie JF, Sherman W (2010) Analysis and comparison of 2D fingerprints: insights into database screening performance using eight fingerprint methods. J Mol Graph Model 29:157-170
31. Hall LH, Kier LB (1995) Electrotopological state indices for atom types: a novel combination of electronic, topological, and valence State Information. J Chem Inf Comput Sci 35:1039-1045
32. Tanimoto TT (1958) An elementary mathematical theory of classification and prediction
33. Cecchini M, Kolb P, Majeux N, Caflisch A (2004) Automated docking of highly flexible ligands by genetic algorithms: a critical assessment. J Comput Chem 25:412-422
34. Jones G, Willett P, Glen RC (1995) Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J Mol Biol 245:43-53
35. Halgren TA, Murphy RB, Friesner RA, Beard HS, Frye LL, Pollard WT, Banks JL (2004) Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J Med Chem 47:1750-1759
36. Yabuuchi H, Niijima S, Takematsu H, Ida T, Hirokawa T, Hara T, Ogawa T, Minowa Y, Tsujimoto G, Okuno Y (2011) Analysis of multiple compound-protein interactions reveals novel bioactive molecules. Mol Syst Biol 7:472
37. R Core Team (2014) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna