Journal of Computer-Aided Molecular Design

, Volume 25, Issue 11, pp 1033–1051

Improving molecular docking through eHiTS’ tunable scoring function



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.


eHiTS Docking Screening Binding affinity Scoring function Score tuning 



High throughput screening


Directory of useful decoys


Interaction surface point




Root mean square deviation


Receiver operating characteristic


Area under the curve

Supplementary material

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

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.SimBioSys Inc.TorontoCanada

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