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Tytuł:
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FWAVina: A novel optimization algorithm for protein-ligand docking based on the fireworks algorithm.
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Autorzy:
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Li J; Key Laboratory of Medical Electrophysiology of Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research and School of Medical Information and Engineering, Southwest Medical University, Luzhou 646000, China; College of Computer and Information Science, Southwest University, Chongqing 400715, China.
Song Y; Luzhou High School, Luzhou 646000, China.
Li F; Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science, Tsinghua University, Beijing 100084, China.
Zhang H; Key Laboratory of Medical Electrophysiology of Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research and School of Medical Information and Engineering, Southwest Medical University, Luzhou 646000, China; Biological Physics Group, School of Physics and Astronomy, The University of Manchester, Manchester, United Kingdom.
Liu W; Key Laboratory of Medical Electrophysiology of Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research and School of Medical Information and Engineering, Southwest Medical University, Luzhou 646000, China. Electronic address: .
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Źródło:
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Computational biology and chemistry [Comput Biol Chem] 2020 Oct; Vol. 88, pp. 107363. Date of Electronic Publication: 2020 Aug 20.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Publication: Oxford : Elsevier
Original Publication: Oxford : Pergamon, c2003-
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MeSH Terms:
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Algorithms*
Molecular Docking Simulation*
Proteins/*chemistry
Ligands
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Contributed Indexing:
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Keywords: Autodock Vina; Broyden-Fletcher-Goldfarb-Shannon; Fireworks algorithm; Molecular docking; Pose search
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Substance Nomenclature:
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0 (Ligands)
0 (Proteins)
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Entry Date(s):
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Date Created: 20200830 Date Completed: 20210520 Latest Revision: 20210520
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Update Code:
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20240105
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DOI:
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10.1016/j.compbiolchem.2020.107363
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PMID:
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32861160
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Protein-ligand docking is an essential process that has accelerated drug discovery. How to accurately and effectively optimize the predominant position and orientation of ligands in the binding pocket of a target protein is a major challenge. This paper proposed a novel ligand binding pose search method called FWAVina based on the fireworks algorithm, which combined the fireworks algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon local search method adopted in AutoDock Vina to address the pose search problem in docking. The FWA was used as a global optimizer to rapidly search promising poses, and the Broyden-Fletcher-Goldfarb-Shannon method was incorporated into FWAVina to perform an exact local search. FWAVina was developed and tested on the PDBbind and DUD-E datasets. The docking performance of FWAVina was compared with the original Vina program. The results showed that FWAVina achieves a remarkable execution time reduction of more than 50 % than Vina without compromising the prediction accuracies in the docking and virtual screening experiments. In addition, the increase in the number of ligand rotatable bonds has almost no effect on the efficiency of FWAVina. The higher accuracy, faster convergence and improved stability make the FWAVina method a better choice of docking tool for computer-aided drug design. The source code is available at https://github.com/eddyblue/FWAVina/.
(Copyright © 2020 Elsevier Ltd. All rights reserved.)
