  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.
