The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Authors: Lorenzo Casalino, Abigail Dommer, Zied Gaieb, Emilia
P. Barros, Terra Stzain, and Surl-Hee Ahn (University of California,
San Diego); Anda Trifan (University of Illinois); Alexander Brace
(Argonne National Laboratory (ANL)); Anthony Bogetti (University of
Pittsburgh); Heng Ma (Argonne National Laboratory (ANL)); Hyungro
Lee and Matteo Turilli (Rutgers University); Syma Khalid (University
of Southampton); Lillian Chong (University of Pittsburgh); Carlos
Simmerling (Stony Brook University); David Hardy, Julio Maia, and
James Phillips (University of Illinois); Thorsten Kurth and Abraham
Stern (Nvidia Corporation); Lei Huang and John McCalpin (University
of Texas); Mahidhar Tatineni (San Diego Supercomputer Center); Tom
Gibbs (Nvidia Corporation); John Stone (University of Illinois);
Shantenu Jha (Brookhaven National Laboratory); Arvind Ramanathan
(Argonne National Laboratory (ANL)); and Rommie E Amaro (University
of California, San Diego)
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’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.
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