Abstract
The performance of all four GOLD scoring functions has been evaluated for pose prediction and virtual screening under the standardized conditions of the comparative docking and scoring experiment reported in this Edition. Excellent pose prediction and good virtual screening performance was demonstrated using unmodified protein models and default parameter settings. The best performing scoring function for both pose prediction and virtual screening was demonstrated to be the recently introduced scoring function ChemPLP. We conclude that existing docking programs already perform close to optimally in the cognate pose prediction experiments currently carried out and that more stringent pose prediction tests should be used in the future. These should employ cross-docking sets. Evaluation of virtual screening performance remains problematic and much remains to be done to improve the usefulness of publically available active and decoy sets for virtual screening. Finally we suggest that, for certain target/scoring function combinations, good enrichment may sometimes be a consequence of 2D property recognition rather than a modelling of the correct 3D interactions.
This is a preview of subscription content, access via your institution.









Abbreviations
- CCDC:
-
Cambridge Crystallographic Data Centre
- PDB:
-
Protein Data Bank
- RMSD:
-
Root mean square deviation
- VS:
-
Virtual screening
- ROC:
-
Receiver operating characteristic
- AUC:
-
Area under curve
- DUD:
-
Directory of useful decoys
References
Jones G, Willett GP, Glen RC (1995) J Mol Biol 245:43–53
Jones G, Willett P, Glen RC, Leach AR, Taylor RJ (1997) Mol Biol 267:727–748
Sousa SJ, Alexandrino PS, Ramos MJ (2006) PROTEINS 65:15–26
Eldridge MD, Murray CW, Auton TR, Paolini GV, Mee RP (1997) J Comput Aided Mol Des 11:425–445
Verdonk ML, Cole JC, Hartshorn MJ, Murray CW, Taylor RD (2003) PROTEINS 52:609–623
Mooij WTM, Verdonk M (2005) PROTEINS 61:272–287
Korb O, Stützle T, Exner TE (2009) J Chem Inf Model 49(1):84–96
Hartshorn MJ, Verdonk ML, Chessari G, Brewerton SC, Mooij WTM, Mortensen PN, Murray CW (2007) J Med Chem 50:726–741
Hendlich M, Bergner A, Günther J, Klebe G (2003) J Mol Biol 326:607–620
Verdonk ML, Chessari G, Cole JC, Hartshorn MJ, Murray CW, Nissink JWM, Taylor RD, Taylor R (2005) J Med Chem 48:6504–6515
Huang N, Shoichet BK, Irwin JJ (2006) J Med Chem 49:6789–6801
Good AC, Oprea TI (2008) J Comput Aided Mol Des 22:169–178
Dönneke D, Schweintz A, Stürzebecher A, Steinmetzer P, Schuster M, Stürzebecher U, Nicklisch S, Stürzebecher J, Steinmetzer T (2007) Bioorg & Med Chem Lett 17:3322–3329
Bender A, Glen RC (2005) J Chem Inf Model 45(5):1369–1375
Verdonk M, Giangreco I, Hall R, Korb O, Mortensen P, Murray CW (2011) J Med Chem 54:5422–5431
Sutherland SJ, Nandigam RK, Erikson JA, Vieth M (2007) J Chem Inf Model 47:2293–2302
Verdonk ML, Mortenson PN, Hall RJ, Hartshorn MJ, Murray CW (2008) J Chem Inf Model 48:2214–2225
Sherman W, Day T, Jacobson MP, Friesner RA, Farid R (2006) J Med Chem 49(20):534–553
Jain AN (2009) J Comput Aided Mol Des 23:355–374
Acknowledgments
This work was performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England. We also thank Dr Colin Groom for valuable comments regarding the manuscript.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Liebeschuetz, J.W., Cole, J.C. & Korb, O. Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test. J Comput Aided Mol Des 26, 737–748 (2012). https://doi.org/10.1007/s10822-012-9551-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10822-012-9551-4
Keywords
- Docking
- Enrichment
- Pose-prediction
- Virtual screening
- GOLD
- Scoring function