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

TL;DR

This paper details the porting and optimization of AutoDock-GPU for the Summit supercomputer, enabling large-scale, high-throughput drug docking simulations to accelerate COVID-19 research.

Contribution

It introduces a high-performance GPU-accelerated docking tool optimized for Summit, facilitating rapid screening of drug compounds against SARS-CoV-2.

Findings

Successful porting and validation of AutoDock-GPU on Summit

Significant speedup in docking calculations

Application to COVID-19 drug discovery efforts

Abstract

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.