Ultra-fast FFT protein docking on graphics processors

David Ritchie 1 Vishwesh Venkatraman 1
1 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Motivation: Modelling protein-protein interactions (PPIs) is an increasingly important aspect of structural bioinformatics. However, predicting PPIs using in silico docking techniques is computationally very expensive. Developing very fast protein docking tools will be useful for studying large-scale PPI networks, and could contribute to the rational design of new drugs. Results: The Hex spherical polar Fourier protein docking algorithm has been implemented on Nvidia graphics processor units (GPUs). On a GTX 285 GPU, an exhaustive and densely sampled six-dimensional (6D) docking search can be calculated in just 15 seconds using multiple one-dimensional (1D) fast Fourier transforms (FFTs). This represents a 45-fold speed-up over the corresponding calculation on a single CPU, being at least two orders of magnitude times faster than a similar CPU calculation using ZDOCK 3.0.1, and estimated to be at least three orders of magnitude faster than the GPU-accelerated version of PIPER on comparable hardware. Hence, for the first time, exhaustive FFT-based protein docking calculations may now be performed in a matter of seconds on a contemporary GPU. Three-dimensional (3D) Hex FFT correlations are also accelerated by the GPU, but the speed-up factor of only 2.5 is much less than that obtained with 1D FFTs. Thus the Hex algorithm appears to be especially well suited to exploit GPUs compared to conventional 3D FFT docking approaches.
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Bioinformatics, Oxford University Press (OUP), 2010, 26 (19), pp.2398-2405. 〈10.1093/bioinformatics/btq444〉
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Contributeur : David Ritchie <>
Soumis le : vendredi 19 novembre 2010 - 20:18:38
Dernière modification le : jeudi 11 janvier 2018 - 06:19:54

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David Ritchie, Vishwesh Venkatraman. Ultra-fast FFT protein docking on graphics processors. Bioinformatics, Oxford University Press (OUP), 2010, 26 (19), pp.2398-2405. 〈10.1093/bioinformatics/btq444〉. 〈inria-00537988〉

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