UM
PSOVina: The hybrid particle swarm optimization algorithm for protein–ligand docking
Marcus C. K. Ng; Simon Fong; Shirley W. I. Siu
2015-03-23
Conference Name5th International Conference on Computational Systems-Biology and Bioinformatics (CSBio)
Source PublicationJournal of Bioinformatics and Computational Biology
Volume13
Issue3
Conference DateNOV 10-12, 2014
Conference PlaceNanyang Technological University, Singapore, SINGAPORE
PublisherIMPERIAL COLLEGE PRESS, 57 SHELTON ST, COVENT GARDEN, LONDON WC2H 9HE, ENGLAND
Abstract

Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein-ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51-60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein-ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo.

KeywordAutodock Conformational Search Drug Design Flexible Docking Particle Swarm Optimization Protein-ligand Docking
DOIhttps://doi.org/10.1142/S0219720015410073
URLView the original
Indexed BySCIE
Language英语
WOS Research AreaBiochemistry & Molecular Biology ; Computer Science ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Computer Science, Interdisciplinary Applications ; Mathematical & Computational Biology
WOS IDWOS:000369757200008
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Cited Times [WOS]:29   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
AffiliationDepartment of Computer and Information Science, University of Macau Avenida da Universidade, Taipa Macau S.A.R, P. R. China
First Author AffilicationUniversity of Macau
Recommended Citation
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Marcus C. K. Ng,Simon Fong,Shirley W. I. Siu. PSOVina: The hybrid particle swarm optimization algorithm for protein–ligand docking[C]:IMPERIAL COLLEGE PRESS, 57 SHELTON ST, COVENT GARDEN, LONDON WC2H 9HE, ENGLAND,2015.
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