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Improving molecular docking through eHiTS’ tunable scoring function

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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.

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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

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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.

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Authors and Affiliations

  1. SimBioSys Inc., 135 Queen’s Plate Dr. Unit 520, Toronto, ON, M9W 6V1, Canada

    Orr Ravitz, Zsolt Zsoldos & Aniko Simon

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  1. Orr Ravitz
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  2. Zsolt Zsoldos
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Correspondence to Orr Ravitz.

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Ravitz, O., Zsoldos, Z. & Simon, A. Improving molecular docking through eHiTS’ tunable scoring function. J Comput Aided Mol Des 25, 1033–1051 (2011). https://doi.org/10.1007/s10822-011-9482-5

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