GPU-Accelerated High-Accuracy Molecular Docking using Guided Differential Evolution

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

The objective in molecular docking is to determine the best binding mode of two molecules in silico. A common applica- tion of molecular docking is in drug discovery where a large number of ligands are docked against a protein to identify potential drug candidates. This is a computationally in- tensive problem especially if flexibility of the molecules are taken into account. In this paper we show how MolDock, which is a high accuracy method for flexible molecular dock- ing using a variant of differential evolution, can be paral- lelised on both CPU and GPU. The methods presented for parallelising the workload result in an average speedup of 3.9x on a 4-core CPU and 27.4x on a comparable CUDA enabled GPU when docking 133 ligands of different sizes. Furthermore, the presented parallelisation schemes are gen- erally applicable and can easily be adapted to other common flexible docking methods.
Original languageEnglish
Title of host publicationGECCO'11 Proceedings of the 13th annual conference on Genetic and evolutionary computation
Number of pages8
PublisherAssociation for Computing Machinery
Publication year2011
Pages1803-1810
ISBN (print)978-1-4503-0557-0
DOIs
Publication statusPublished - 2011

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