2434

Fast binding site mapping using GPUs and CUDA

Bharat Sukhwani, Martin C. Herbordt
Computer Architecture and Automated Design Laboratory, Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215
In 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW) (April 2010), pp. 1-8.

@conference{sukhwani2010fast,

   title={Fast binding site mapping using gpus and cuda},

   author={Sukhwani, B. and Herbordt, M.C.},

   booktitle={Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), 2010 IEEE International Symposium on},

   pages={1–8},

   year={2010},

   organization={IEEE}

}

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Binding site mapping refers to the computational prediction of the regions on a protein surface that are likely to bind a small molecule with high affinity. The process involves flexibly docking a variety of small molecule probes and finding a consensus site that binds most of those probes. Due to the computational complexity of flexible docking, the process is often split into two steps: the first performs rigid docking between the protein and the probe; the second models the side chain flexibility by energy-minimizing the (few thousand) top scoring protein-probe complexes generated by the first step. Both these steps are computationally very expensive, requiring many hours of runtime per probe on a serial CPU. In the current article, we accelerate a production mapping software program using NVIDIA GPUs. We accelerate both the rigid-docking and the energy minimization steps of the program. The result is a 30x speedup on rigid docking and 12x on energy minimization, resulting in a 13x overall speedup over the current single core implementation.
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