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

Publication Type
Conference Paper
Journal Name
ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)
Book Title
BCB '20: Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
Publication Date
Page Number
Conference Name
11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)
Conference Location
Virtual, Georgia, United States of America
Conference Sponsor
ACM, SigBio
Conference Date

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.