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

  1. Lorenzo Casalino
  2. Abigail C Dommer
  3. Zied Gaieb
  4. Emilia P Barros
  5. Terra Sztain
  6. Surl-Hee Ahn
  7. Anda Trifan
  8. Alexander Brace
  9. Anthony T Bogetti
  10. Austin Clyde
  11. Heng Ma
  12. Hyungro Lee
  13. Matteo Turilli
  14. Syma Khalid
  15. Lillian T Chong
  16. Carlos Simmerling
  17. David J Hardy
  18. Julio DC Maia
  19. James C Phillips
  20. Thorsten Kurth
  21. Abraham C Stern
  22. Lei Huang
  23. John D McCalpin
  24. Mahidhar Tatineni
  25. Tom Gibbs
  26. John E Stone
  27. Shantenu Jha
  28. Arvind Ramanathan
  29. Rommie E Amaro

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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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  1. Version published to 10.1177/10943420211006452
  2. ScreenIT

    SciScore for 10.1101/2020.11.19.390187: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.11.19.390187v1 on bioRxiv