AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics

@article{Casalino2020AIDrivenMS,
  title={AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics},
  author={Lorenzo Casalino and Abigail C. Dommer and Zied Gaieb and Em{\'i}lia P. Barros and Terra Sztain and Surl-Hee Ahn and Anda Trifan and Alexander Brace and Anthony T. Bogetti and Heng Ma and Hyungro Lee and Matteo Turilli and Syma Khalid and Lillian T. Chong and Carlos Simmerling and David J. Hardy and Julio D C Maia and James C. Phillips and Thorsten Kurth and Abraham Stern and Lei Huang and John D. McCalpin and Mahidhar Tatineni and Tom Gibbs and John E. Stone and Shantenu Jha and Arvind Ramanathan and Rommie E. Amaro},
  journal={bioRxiv},
  year={2020}
}
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… 

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