Allosteric Inhibition of the SARS‐CoV‐2 Main Protease: Insights from Mass Spectrometry Based Assays**

  1. Tarick J. El‐Baba
  2. Corinne A. Lutomski
  3. Anastassia L. Kantsadi
  4. Tika R. Malla
  5. Tobias John
  6. Victor Mikhailov
  7. Jani R. Bolla
  8. Christopher J. Schofield
  9. Nicole Zitzmann
  10. Ioannis Vakonakis
  11. Carol V. Robinson

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Abstract

The SARS‐CoV‐2 main protease (M pro ) cleaves along the two viral polypeptides to release non‐structural proteins required for viral replication. M Pro is an attractive target for antiviral therapies to combat the coronavirus‐2019 disease. Here, we used native mass spectrometry to characterize the functional unit of M pro . Analysis of the monomer/dimer equilibria reveals a dissociation constant of K d =0.14±0.03 μM, indicating M Pro has a strong preference to dimerize in solution. We characterized substrate turnover rates by following temporal changes in the enzyme‐substrate complexes, and screened small molecules, that bind distant from the active site, for their ability to modulate activity. These compounds, including one proposed to disrupt the dimer, slow the rate of substrate processing by ≈35 %. This information, together with analysis of the x ‐ray crystal structures, provides a starting point for the development of more potent molecules that allosterically regulate M Pro activity.

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  1. Version published to 10.1002/ange.202010316
  2. ScreenIT

    SciScore for 10.1101/2020.07.29.226761: (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

    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.

  3. ScreenIT

    SciScore for 10.1101/2020.07.29.226761: (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

    Software and Algorithms
    SentencesResources
    TJ was supported by the Oxford-GSK-Crick Doctoral Program in Chemical Biology, EPSRC (EP/R512060/1) and GlaxoSmithKline. C.J.S. thanks the Wellcome Trust and the Medical Research Council for support.
    Oxford-GSK-Crick Doctoral Program
    suggested: None

    Data from additional tools added to each annotation on a weekly basis.

    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.

  4. Version published to 10.1101/2020.07.29.226761v1 on bioRxiv