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Scalable HPC and AI Infrastructure for COVID-19 Therapeutics

Authors :
Lee, Hyungro
Merzky, Andre
Tan, Li
Titov, Mikhail
Turilli, Matteo
Alfe, Dario
Bhati, Agastya
Brace, Alex
Clyde, Austin
Coveney, Peter
Ma, Heng
Ramanathan, Arvind
Stevens, Rick
Trifan, Anda
Van Dam, Hubertus
Wan, Shunzhou
Wilkinson, Sean
Jha, Shantenu
Publication Year :
2020

Abstract

COVID-19 has claimed more 1 million lives and resulted in over 40 million infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. In response, the DOE recently established the Medical Therapeutics project as part of the National Virtual Biotechnology Laboratory, and tasked it with creating the computational infrastructure and methods necessary to advance therapeutics development. We discuss innovations in computational infrastructure and methods that are accelerating and advancing drug design. Specifically, we describe several methods that integrate artificial intelligence and simulation-based approaches, and the design of computational infrastructure to support these methods at scale. We discuss their implementation and characterize their performance, and highlight science advances that these capabilities have enabled.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2010.10517
Document Type :
Working Paper