GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research

被引:30
作者
LeGrand, Scott [1 ]
Scheinberg, Aaron [2 ]
Tillack, Andreas F. [3 ]
Thavappiragasam, Mathialakan [4 ]
Vermaas, Josh V. [4 ]
Agarwal, Rupesh [5 ]
Larkin, Jeff [1 ]
Poole, Duncan [1 ]
Santos-Martins, Diogo [3 ]
Solis-Vasquez, Leonardo [6 ]
Koch, Andreas [6 ]
Forli, Stefano [3 ]
Hernandez, Oscar [4 ]
Smith, Jeremy C. [5 ,7 ]
Sedova, Ada [4 ]
机构
[1] NVIDIA Corp, Santa Clara, CA USA
[2] Jubilee Dev, Cambridge, MA USA
[3] Scripps Res, La Jolla, CA USA
[4] Oak Ridge Natl Lab, Oak Ridge, TN 37830 USA
[5] Univ Tennessee, Knoxville, TN USA
[6] Tech Univ Darmstadt, Darmstadt, Germany
[7] UT ORNL, Oak Ridge, TN USA
来源
ACM-BCB 2020 - 11TH ACM CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY, AND HEALTH INFORMATICS | 2020年
基金
美国国家卫生研究院;
关键词
Drug discovery; high-performance computing; GPU acceleration; protein-ligand docking; MOLECULAR DOCKING; AUTOMATED DOCKING; SYSTEM;
D O I
10.1145/3388440.3412472
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Protein-ligand docking is an in silico tool used to screen potential drug compounds for their ability to bind to a given protein receptor within a drug-discovery campaign. Experimental drug screening is expensive and time consuming, and it is desirable to carry out large scale docking calculations in a high-throughput manner to narrow the experimental search space. Few of the existing computational docking tools were designed with high performance computing in mind. Therefore, optimizations to maximize use of high-performance computational resources available at leadership-class computing facilities enables these facilities to be leveraged for drug discovery. Here we present the porting, optimization, and validation of the AutoDock-GPU program for the Summit supercomputer, and its application to initial compound screening efforts to target proteins of the SARS-CoV-2 virus responsible for the current COVID-19 pandemic.
引用
收藏
页数:10
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