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

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

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research
Creator	Agarwal, Forli, Stefano Hernandez, Oscar Koch, Andreas Larkin, Jeff Legrand, Scott Poole, Duncan Ridge, Oak Santos-Martins, Diogo Scheinberg, Aaron Sedova, Ada Smith, Jeremy Solis-Vasquez, Leonardo Tennessee, Tennessee, Rupesh Tillack, Andreas Vermaas, Josh
topic	covid:f07902c43f653318afb88c8f85d1251790099145#this
Source	ArXiv
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.
has issue date	2020-07-06(xsd:dateTime)
has license	arxiv
sha1sum (hex)	f07902c43f653318afb88c8f85d1251790099145
resource representing a document's title	GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research
resource representing a document's body	covid:f07902c43f653318afb88c8f85d1251790099145#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/f07902c43f653318afb88c8f85d1251790099145
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