AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow en...

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Bibliographic Details
Published in:	The international journal of high performance computing applications Vol. 35; no. 5; pp. 432 - 451
Main Authors:	Casalino, Lorenzo, Dommer, Abigail C, Gaieb, Zied, Barros, Emilia P, Sztain, Terra, Ahn, Surl-Hee, Trifan, Anda, Brace, Alexander, Bogetti, Anthony T, Clyde, Austin, Ma, Heng, Lee, Hyungro, Turilli, Matteo, Khalid, Syma, Chong, Lillian T, Simmerling, Carlos, Hardy, David J, Maia, Julio DC, Phillips, James C, Kurth, Thorsten, Stern, Abraham C, Huang, Lei, McCalpin, John D, Tatineni, Mahidhar, Gibbs, Tom, Stone, John E, Jha, Shantenu, Ramanathan, Arvind, Amaro, Rommie E
Format:	Journal Article
Language:	English
Published:	London, England SAGE Publications 01-09-2021 SAGE PUBLICATIONS, INC SAGE
Subjects:	AI BASIC BIOLOGICAL SCIENCES computational virology COVID19 deep learning Glycan GPU HPC MATHEMATICS AND COMPUTING Molecular dynamics multiscale simulation SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 Special Issue Papers Viral diseases weighted ensemble Workflow deep learning weighted ensemble computational virology SARS-CoV-2 COVID19 Molecular dynamics AI HPC multiscale simulation GPU
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Summary:	We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike’s full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 BNL-221640-2021-JAAM SC0012704; GM132826; MCB-2032054 National Science Foundation (NSF) Coronavirus CARES Act National Institutes of Health (NIH) USDOE Office of Science (SC), Advanced Scientific Computing Research (SC-21)
ISSN:	1094-3420 1741-2846
DOI:	10.1177/10943420211006452