Accelerating Molecular Docking Calculations Using Graphics Processing Units

Oliver Korb, Thomas Stutzle, Thomas E. Exner
Cambridge Crystallographic Data Centre, CB2 1EZ Cambridge, United Kingdom
Journal of Chemical Information and Modeling


   author={Korb, Oliver and Stutzle, Thomas and Exner, Thomas E.}


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The generation of molecular conformations and the evaluation of interaction potentials are common tasks in molecular modeling applications, particularly in protein-ligand or protein-protein docking programs. In this work, we present a GPU-accelerated approach capable of speeding up these tasks considerably. For the evaluation of interaction potentials in the context of rigid protein-protein docking, the GPU-accelerated approach reached speedup factors of up to over 50 compared to an optimized CPU-based implementation. Treating the ligand and donor groups in the protein binding site as flexible, speedup factors of up to 16 can be observed in the evaluation of protein-ligand interaction potentials. Additionally, we introduce a parallel version of our protein-ligand docking algorithm PLANTS that can take advantage of this GPU-accelerated scoring function evaluation. We compared the GPU-accelerated parallel version to the same algorithm running on the CPU and also to the highly optimized sequential CPU-based version. In terms of dependence of the ligand size and the number of rotatable bonds, speedup factors of up to 10 and 7, respectively, can be observed. Finally, a fitness landscape analysis in the context of rigid protein-protein docking was performed. Using a systematic grid-based search methodology, the GPU-accelerated version outperformed the CPU-based version with speedup factors of up to 60.
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