METADOCK 2: A high-throughput parallel metaheuristic scheme for molecular docking.

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ID: 85489
2020
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Abstract
Molecular docking methods are extensively used to predict the interaction between protein-ligand systems in terms of structure and binding affinity, through the optimization of a physics-based scoring function. However, the computational requirements of these simulations grow exponentially with: (1) the global optimization procedure, (2) the number and degrees of freedom of molecular conformations generated, and (3) the mathematical complexity of the scoring function.In this work we introduce a novel molecular docking method named METADOCK 2, which incorporates several novel features such as (1) a ligand-dependent blind docking approach that exhaustively scans the whole protein surface to detect novel allosteric sites, (2) an optimization method to enable the use of a wide branch of metaheuristics, and (3) a heterogeneous implementation based on multicore CPUs and multiple Graphics Processing Units (GPUs). Two representative scoring functions implemented in METADOCK 2 are extensively evaluated in terms of computational performance and accuracy using several benchmarks (such as the well-known DUD) against AutoDock 4.2 and AutoDock Vina.Results place METADOCK 2 as an efficient and accurate docking methodology able to deal with complex systems where computational demands are staggering and which outperforms both AutoDock Vina and AutoDock 4.https://Baldoimbernon@bitbucket.org/Baldoimbernon/metadock_2.git.Supplementary data are available at Bioinformatics online.
Reference Key
imbernn2020metadockbioinformatics Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Imbernón, Baldomero;Serrano, Antonio;Bueno-Crespo, Andrés;Abellán, José L;Pérez-Sánchez, Horacio;Cecilia, José M;
Journal Bioinformatics
Year 2020
DOI
btz958
URL
Keywords
cardiac resynchronization therapy atrioventricular delay biventricular pacing left ventricular remodeling

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