@article{b332741dd2d7424b999249b0cdbf909d,
title = "AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics",
abstract = "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{\textquoteright}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.",
keywords = "AI, computational virology, COVID19, deep learning, GPU, HPC, Molecular dynamics, multiscale simulation, SARS-CoV-2, weighted ensemble",
author = "Lorenzo Casalino and Dommer, {Abigail C.} and Zied Gaieb and Barros, {Emilia P.} and Terra Sztain and Ahn, {Surl Hee} and Anda Trifan and Alexander Brace and Bogetti, {Anthony T.} and Austin Clyde and Heng Ma and Hyungro Lee and Matteo Turilli and Syma Khalid and Chong, {Lillian T.} and Carlos Simmerling and Hardy, {David J.} and Maia, {Julio D.C.} and Phillips, {James C.} and Thorsten Kurth and Stern, {Abraham C.} and Lei Huang and McCalpin, {John D.} and Mahidhar Tatineni and Tom Gibbs and Stone, {John E.} and Shantenu Jha and Arvind Ramanathan and Amaro, {Rommie E.}",
note = "Funding Information: The authors thank D. Maxwell, B. Messer, J. Vermaas, and the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory supported by the DOE under Contract DE-AC05-00OR22725. We also thank the Texas Advanced Computing Center Frontera team, especially D. Stanzione and T. Cockerill, and for compute time made available through a Director{\textquoteright}s Discretionary Allocation (NSF OAC-1818253). We thank the Argonne Leadership Computing Facility supported by the DOE under DE-AC02-06CH11357. NAMD and VMD are funded by NIH P41-GM104601. The NAMD team thanks Intel and M. Brown for contributing the AVX-512 tile list kernels. Anda Trifan acknowledges support from a DOE CSGF (DE-SC0019323). Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by NIH GM132826, NSF RAPID MCB-2032054, an award from the RCSA Research Corp., a UC San Diego Moore{\textquoteright}s Cancer Center 2020 SARS-COV-2 seed grant, to R.E.A. This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the US DOE Office of Science and the National Nuclear Security Administration. Research was supported by the DOE through the National Virtual Biotechnology Laboratory, a consortium of DOE national laboratories focused on response to COVID-19, with funding from the Coronavirus CARES Act. This work was supported by the NIH (1R01GM115805-01) to L.T.C. Funding Information: The authors thank D. Maxwell, B. Messer, J. Vermaas, and the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory supported by the DOE under Contract DE-AC05-00OR22725. We also thank the Texas Advanced Computing Center Frontera team, especially D. Stanzione and T. Cockerill, and for compute time made available through a Director?s Discretionary Allocation (NSF OAC-1818253). We thank the Argonne Leadership Computing Facility supported by the DOE under DE-AC02-06CH11357. NAMD and VMD are funded by NIH P41-GM104601. The NAMD team thanks Intel and M. Brown for contributing the AVX-512 tile list kernels. Anda Trifan acknowledges support from a DOE CSGF (DE-SC0019323). The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by NIH GM132826, NSF RAPID MCB-2032054, an award from the RCSA Research Corp., a UC San Diego Moore?s Cancer Center 2020 SARS-COV-2 seed grant, to R.E.A. This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the US DOE Office of Science and the National Nuclear Security Administration. Research was supported by the DOE through the National Virtual Biotechnology Laboratory, a consortium of DOE national laboratories focused on response to COVID-19, with funding from the Coronavirus CARES Act. This work was supported by the NIH (1R01GM115805-01) to L.T.C. Publisher Copyright: {\textcopyright} The Author(s) 2021.",
year = "2021",
month = sep,
doi = "10.1101/2020.11.19.390187",
language = "English (US)",
volume = "35",
pages = "432--451",
journal = "International Journal of High Performance Computing Applications",
issn = "1094-3420",
publisher = "SAGE Publishing",
number = "5",
}