Journal of Computer-Aided Molecular Design

, Volume 25, Issue 11, pp 1033–1051 | Cite as

Improving molecular docking through eHiTS’ tunable scoring function

Article

Abstract

We present three complementary approaches for score-tuning that improve docking performance in pose prediction, virtual screening and binding affinity assessment. The methodology utilizes experimental data to customize the scoring function for the system of interest considering the specific docking scenario. The tuning approach, which has been implemented as an automated utility in eHiTS, is introduced as a solution to one of the conundrums of the molecular docking paradigm, namely, the lack of a universally well performing scoring function. The accuracy of scoring functions has been shown to be generally system-dependent, and particularly lacking for binding energy and bio-activity predictions. In the proposed approach, pose and energy predictions are enhanced by adjusting the relative weights of the eHiTS energy terms to improve score-RMSD or score-affinity correlations. In a virtual screening context ligand-based similarity is used to rescale the docking score such that better enrichment factors are achieved. We discuss the algorithmic details of the methods, and demonstrate the effects of score tuning on a variety of targets, including CDK2, BACE1 and neuraminidase, as well as on the popular benchmarks—the Directory of Useful Decoys and the PDBBind database.

Keywords

eHiTS Docking Screening Binding affinity Scoring function Score tuning 

Abbreviations

HTS

High throughput screening

DUD

Directory of useful decoys

ISP

Interaction surface point

NA

Neuraminidase

RMSD

Root mean square deviation

ROC

Receiver operating characteristic

AUC

Area under the curve

Notes

Acknowledgments

The authors thank Bashir Sadjad for his diligent coding during the work on this project. We also thank Dan Harris for his application development of a previous version of the eHiTS tuning utility and Tony Cook for reviewing an earlier version of this manuscript. We acknowledge Jason Cross and coauthors for permission to reproduce data from their paper.

Supplementary material

10822_2011_9482_MOESM1_ESM.pdf (1.1 mb)
Supplementary material 1 (PDF 1118 kb)

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.SimBioSys Inc.TorontoCanada

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