Letter

Reranking Docking Poses Using Molecular Simulations and Approximate Free Energy Methods

Dipartimento di Farmacia, Università degli Studi di Salerno, Via Giovanni Paolo II 132, 84084 Fisciano (SA), Italy
Computational Biophysics Laboratory (GRIB-IMIM), Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), C/Doctor Aiguader 88, 08003 Barcelona, Spain
§ InhibOx Limited, Oxford Centre for Innovation, New Road, Oxford OX1 1BY, United Kingdom
Acellera, Barcelona Biomedical Research Park (PRBB), C/Doctor Aiguader 88, 08003 Barcelona, Spain
Department of Applied Computing, University of Buckingham, Hunter Street, Buckingham MK18 1EG, United Kingdom
# InhibOx Limited, Oxford Centre for Innovation, New Road, Oxford OX1 1BY, United Kingdom
J. Chem. Inf. Model., 2014, 54 (8), pp 2185–2189
DOI: 10.1021/ci500309a
Publication Date (Web): July 21, 2014
Copyright © 2014 American Chemical Society
*E-mail: paul.finn@buckingham.ac.uk (P.F.)., *E-mail: gianni.defabritiis@upf.edu (G.D.F.).

Abstract

Abstract Image

Fast and accurate identification of active compounds is essential for effective use of virtual screening workflows. Here, we have compared the ligand-ranking efficiency of the linear interaction energy (LIE) method against standard docking approaches. Using a trypsin set of 1549 compounds, we performed 12,250 molecular dynamics simulations. The LIE method proved effective but did not yield results significantly better than those obtained with docking codes. The entire database of simulations is released.

Supporting Information


Details of library design, simulation and docking protocols, erratic compounds, comparison with other LIE parameters, and further analysis of the simulations. This material is available free of charge via the Internet at http://pubs.acs.org.

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Published online 21 July 2014
Published in print 25 August 2014
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