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METADOCK 2: a high-throughput parallel metaheuristic scheme for molecular docking.
- Source :
-
Bioinformatics . Jun2021, Vol. 37 Issue 11, p1515-1520. 6p. - Publication Year :
- 2021
-
Abstract
- Motivation 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: (i) the global optimization procedure, (ii) the number and degrees of freedom of molecular conformations generated and (iii) the mathematical complexity of the scoring function. Results In this work, we introduce a novel molecular docking method named METADOCK 2, which incorporates several novel features, such as (i) a ligand-dependent blind docking approach that exhaustively scans the whole protein surface to detect novel allosteric sites, (ii) an optimization method to enable the use of a wide branch of metaheuristics and (iii) a heterogeneous implementation based on multicore CPUs and multiple graphics processing units. 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. Availability and implementation https://Baldoimbernon@bitbucket.org/Baldoimbernon/metadock%5f2.git. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13674803
- Volume :
- 37
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 151369050
- Full Text :
- https://doi.org/10.1093/bioinformatics/btz958