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      GPU accelerated molecular docking with parallel genetic algorithm

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      Author
      Ouyang, Xuchang
      Kwoh, Chee Keong
      Date of Issue
      2012
      Conference Name
      IEEE International Conference on Parallel and Distributed Systems (18th : 2012 : Singapore)
      School
      School of Computer Engineering
      Research Centre
      Bioinformatics Research Centre
      Abstract
      Molecular docking is a widely used tool in Computer-aided Drug Design and Discovery. Due to the complexity of simulating the chemical events when two molecules interact, highly accelerated molecular docking programs are of great interest and importance for practical use. In this paper, we present a GPU accelerated docking program implemented with CUDA. The hardware-enabled texture interpolation is employed for fast energy evaluation. Two types of parallel genetic algorithms are mapped to the CUDA computing architecture and used for the search of optimal docking result. Comparing to the CPU implementation, the GPU accelerated docking program achieved significant speedup while producing comparable results to the CPU version. The source code is made public at http://code.google.com/p/cudock/.
      Subject
      DRNTU::Engineering::Computer science and engineering
      Type
      Conference Paper
      Rights
      © 2012 IEEE.
      Collections
      • SCSE Conference Papers
      http://dx.doi.org/10.1109/ICPADS.2012.99
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