High-throughput virtual molecular docking with AutoDockCloud

被引:17
|
作者
Ellingson, Sally R. [1 ,2 ]
Baudry, Jerome [1 ,2 ]
机构
[1] Univ Tennessee, Knoxville, TN 37996 USA
[2] UT ORNL Ctr Mol Biophys, Oak Ridge, TN USA
来源
基金
美国国家科学基金会;
关键词
EFFICIENT;
D O I
10.1002/cpe.2926
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Virtual molecular docking is a computational method used in computer-aided drug discovery that calculates the binding affinity of a small molecule drug candidate to a target protein. High-throughput virtual screenings calculate the binding affinities for a large number of molecules at once and ranks potential drug candidates to greatly reduces the time and cost of suggesting new potential pharmaceuticals. This high-throughput screening is a task parallel process and therefore well-suited for distributed computing. In this study, we use the open source Hadoop framework implementing the MapReduce paradigm for distributed computing on a cloud platform and the widely used molecular docking program, AutoDock. The initial implementation of AutoDockCloud showed a speed-up of 450 on Kandinsky, a cloud computer located at Oak Ridge National Laboratory. Further modifications show promise for a greater speed-up of large chemical library screenings and also incorporates and distributes the pre-docking procedures. Copyright © 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:907 / 916
页数:10
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