Abstract
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 language | English |
|---|---|
| Title of host publication | GECCO'11 Proceedings of the 13th annual conference on Genetic and evolutionary computation |
| Number of pages | 8 |
| Publisher | Association for Computing Machinery |
| Publication date | 2011 |
| Pages | 1803-1810 |
| ISBN (Print) | 978-1-4503-0557-0 |
| DOIs | |
| Publication status | Published - 2011 |