Ultra-fast FFT protein docking on graphics processors

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 6D docking search can be calculated in just 15 s using multiple 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 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. AVAILABILITY http://hex.loria.fr/ and http://hexserver.loria.fr/.

[1]  A. Arnold,et al.  Harvesting graphics power for MD simulations , 2007, 0709.3225.

[2]  Dima Kozakov,et al.  Convergence and combination of methods in protein-protein docking. , 2009, Current opinion in structural biology.

[3]  Lazaros Mavridis,et al.  HexServer: an FFT-based protein docking server powered by graphics processors , 2010, Nucleic Acids Res..

[4]  Martin C. Herbordt,et al.  GPU acceleration of a production molecular docking code , 2009, GPGPU-2.

[5]  David Kaeli,et al.  Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units , 2009 .

[6]  Jens H. Krüger,et al.  A Survey of General‐Purpose Computation on Graphics Hardware , 2007, Eurographics.

[7]  Pat Hanrahan,et al.  Brook for GPUs: stream computing on graphics hardware , 2004, SIGGRAPH 2004.

[8]  David Ritchie,et al.  High-order analytic translation matrix elements for real-space six-dimensional polar Fourier correlations , 2005 .

[9]  Ruben Abagyan,et al.  FRODOCK: a new approach for fast rotational protein-protein docking , 2009, Bioinform..

[10]  Stephen R. Comeau,et al.  PIPER: An FFT‐based protein docking program with pairwise potentials , 2006, Proteins.

[11]  Klaus Schulten,et al.  Accelerating Molecular Modeling Applications with GPU Computing , 2009 .

[12]  Andreas Hildebrandt,et al.  Highly accelerated feature detection in proteomics data sets using modern graphics processing units , 2009, Bioinform..

[13]  M. Sternberg,et al.  Modelling protein docking using shape complementarity, electrostatics and biochemical information. , 1997, Journal of molecular biology.

[14]  Ruth Nussinov,et al.  Principles of docking: An overview of search algorithms and a guide to scoring functions , 2002, Proteins.

[15]  Satoshi Matsuoka,et al.  Bandwidth intensive 3-D FFT kernel for GPUs using CUDA , 2008, 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis.

[16]  E. Katchalski‐Katzir,et al.  Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Naga K. Govindaraju,et al.  High performance discrete Fourier transforms on graphics processors , 2008, HiPC 2008.

[18]  Amitabh Varshney,et al.  High-throughput sequence alignment using Graphics Processing Units , 2007, BMC Bioinformatics.

[19]  Kentaro Shimizu,et al.  A fast protein-protein docking algorithm using series expansion in terms of spherical basis functions. , 2005, Genome informatics. International Conference on Genome Informatics.

[20]  L. Biedenharn.  Angular momentum in quantum physics , 1981 .

[21]  Z. Weng,et al.  Protein–protein docking benchmark 2.0: An update , 2005, Proteins.

[22]  Giorgio Valle,et al.  CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment , 2008, BMC Bioinformatics.

[23]  D. Ritchie,et al.  Protein docking using spherical polar Fourier correlations , 2000, Proteins.

[24]  Z. Weng,et al.  Integrating statistical pair potentials into protein complex prediction , 2007, Proteins.

[25]  David W Ritchie,et al.  Recent progress and future directions in protein-protein docking. , 2008, Current protein & peptide science.

[26]  Patricia J. Teller,et al.  Proceedings of the 2008 ACM/IEEE conference on Supercomputing , 2008, HiPC 2008.

[27]  Juan Fernández-Recio,et al.  Pushing Structural Information into the Yeast Interactome by High-Throughput Protein Docking Experiments , 2009, PLoS Comput. Biol..

[28]  Solène Grosdidier,et al.  Computer applications for prediction of protein-protein interactions and rational drug design. , 2009, Advances and applications in bioinformatics and chemistry : AABC.

[29]  D Fischer,et al.  A computer vision based technique for 3-D sequence-independent structural comparison of proteins. , 1993, Protein engineering.

[30]  Z. Weng,et al.  ZDOCK: An initial‐stage protein‐docking algorithm , 2003, Proteins.

[31]  Todd J. Martinez,et al.  Graphical Processing Units for Quantum Chemistry , 2008, Computing in Science & Engineering.

[32]  L. T. Ten Eyck,et al.  Protein docking using continuum electrostatics and geometric fit. , 2001, Protein engineering.

[33]  Zhiping Weng,et al.  A protein–protein docking benchmark , 2003, Proteins.

[34]  Marc A. Suchard,et al.  Many-core algorithms for statistical phylogenetics , 2009, Bioinform..

[35]  Julie C. Mitchell,et al.  CUSA and CUDE: GPU-Accelerated Methods for Estimating Solvent Accessible Surface Area and Desolvation , 2009, J. Comput. Biol..

[36]  Tatsuya Yoshikawa,et al.  Improving the Accuracy of an Affinity Prediction Method by Using Statistics on Shape Complementarity between Proteins , 2009, J. Chem. Inf. Model..

[37]  M. Nilges,et al.  Complementarity of structure ensembles in protein-protein binding. , 2004, Structure.

[38]  David W. Ritchie,et al.  Accelerating and focusing protein-protein docking correlations using multi-dimensional rotational FFT generating functions , 2008, Bioinform..