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Flexible receptor docking for drug discovery

Pages 1189-1200 | Published online: 26 Aug 2015
 

Abstract

Introduction: Molecular docking has become a popular method for virtual screening. Docking small molecules to a rigid biological receptor is fast but could produce many false negatives and identify less diverse compounds. Flexible receptor docking has alleviated this problem.

Areas covered: This article focuses on reviewing ensemble docking as an approximate but inexpensive method to incorporate receptor flexibility in molecular docking. It outlines key features and recent advances of this method and points out problem areas that need to be addressed to make it even more useful in drug discovery.

Expert opinion: Among the different methods introduced for flexible receptor docking, ensemble docking represents one of the most popular approaches, especially for high-throughput virtual screening. One can generate structural ensembles by using experimental structures, by structural modeling and by various types of molecular simulations. In building a structural ensemble, a judicious choice of the structures to be included can improve performance. Furthermore, reducing the size of the structural ensemble can cut computational costs, and removing the structures that can bind few ligands well could enrich the number of true actives identified by ensemble docking. The ability of ensemble docking to identify more true positives at the top of a rank-ordered list also depends on the choice of the methods to score and rank compounds, an area that needs further research.

Acknowledgments

The author acknowledges his students and collaborators with whom he has worked with on some of the research discussed within.

Declaration of interest

CF Wong is financially supported by the National Cancer Institute (Grant No.CA122090), the National Institute of Allergy and Infectious Diseases (Grant No.AI071991) and the Research Board of the University of Missouri System. He is also supported by a Research Award from the University of Missouri-St Louis and the University of Missouri Bioinformatics Consortium. This author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Notes

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