SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome

  1. Maxwell I. Zimmerman
  2. Justin R. Porter
  3. Michael D. Ward
  4. Sukrit Singh
  5. Neha Vithani
  6. Artur Meller
  7. Upasana L. Mallimadugula
  8. Catherine E. Kuhn
  9. Jonathan H. Borowsky
  10. Rafal P. Wiewiora
  11. Matthew F. D. Hurley
  12. Aoife M Harbison
  13. Carl A Fogarty
  14. Joseph E. Coffland
  15. Elisa Fadda
  16. Vincent A. Voelz
  17. John D. Chodera
  18. Gregory R. Bowman

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Abstract

SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression, and replication, which depend on the structure and dynamics of its constituent proteins. Many protein structures have been solved, but far less is known about their relevant conformational changes. To address this challenge, over a million citizen scientists banded together through the Folding@home distributed computing project to create the first exascale computer and simulate an unprecedented 0.1 seconds of the viral proteome. Our simulations capture dramatic opening of the apo Spike complex, far beyond that seen experimentally, which explains and successfully predicts the existence of ‘cryptic’ epitopes. Different Spike homologues modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also observe dramatic conformational changes across the proteome, which reveal over 50 ‘cryptic’ pockets that expand targeting options for the design of antivirals. All data and models are freely available online, providing a quantitative structural atlas.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.27.175430: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    System preparation: All simulations were prepared using Gromacs 2020.60 Initial structures were placed in a dodecahedral box that extends 1.0 nm beyond the protein in any dimension.
    Gromacs
    suggested: (GROMACS, RRID:SCR_014565)
    Simulations were deployed using a simulation core based on either GROMACS 5.0.4 or OpenMM 7.4.1.60,68 To estimate the performance of Folding@home, we make the conservative assumption that each CPU core performs at 0.0127 TFLOPS and each GPU at 1.672 native TFLOPS (or 3.53 X86-equivalent TFLOPS), as explained in our long-standing performance estimate (https://stats.foldingathome.org/os).
    OpenMM
    suggested: (OpenMM, RRID:SCR_000436)
    69 All MSMs were built using our python package, enspara.
    python
    suggested: (IPython, RRID:SCR_001658)
    Conservation was defined as one minus the entropy.
    Conservation
    suggested: (Conservation, RRID:SCR_016064)

    Results from OddPub: Thank you for sharing your data.

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 25 and 11. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.06.27.175430v3 on bioRxiv
  3. Version published to 10.1101/2020.06.27.175430v2 on bioRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.06.27.175430: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    HCoV-NL63, SARS-CoV-1, and SARS-CoV-2 are shown as light-blue, orange, and black, respectively.
    HCoV-NL63
    suggested: CVCL_RW88
    Software and Algorithms
    SentencesResources
    Simulations were deployed using a simulation core based on either GROMACS 5.0.4 or OpenMM 7.4.1.50,58 To estimate the performance of Folding@home, we make the conservative assumption that each CPU core performs at 0.0127 TFLOPS and each GPU at 1.672 native TFLOPS (or 3.53 X86-equivalent TFLOPS), as explained in our long-standing performance estimate (https://stats.foldingathome.org/os).
    GROMACS
    suggested: (GROMACS, SCR_014565)
          <div style="margin-bottom:8px">
        <div><b>OpenMM</b></div>
        <div>suggested: (OpenMM, <a href="https://scicrunch.org/resources/Any/search?q=SCR_000436">SCR_000436</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Solvent accessible surface area calculations were computed using the Shrake-Rupley algorithm as implemented in the python package MDTraj.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>python</b></div>
        <div>suggested: (IPython, <a href="https://scicrunch.org/resources/Any/search?q=SCR_001658">SCR_001658</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Conservation was defined as one minus the entropy.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Conservation</b></div>
        <div>suggested: (Conservation, <a href="https://scicrunch.org/resources/Any/search?q=SCR_016064">SCR_016064</a>)</div>
      </div>
    </td></tr></table>

    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 OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  5. Version published to 10.1101/2020.06.27.175430v1 on bioRxiv