Conserved interactions required for inhibition of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

  1. Alina Shitrit
  2. Daniel Zaidman
  3. Ori Kalid
  4. Itai Bloch
  5. Dvir Doron
  6. Tali Yarnizky
  7. Idit Buch
  8. Idan Segev
  9. Efrat Ben-Zeev
  10. Elad Segev
  11. Oren Kobiler

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Abstract

The COVID-19 pandemic caused by the SARS-CoV-2 requires a fast development of antiviral drugs. SARS-CoV-2 viral main protease (Mpro, also called 3C‐like protease, 3CLpro) is a potential target for drug design. Crystal and co-crystal structures of the SARS-CoV-2 Mpro have been solved, enabling the rational design of inhibitory compounds. In this study we analyzed the available SARS-CoV-2 and the highly similar SARS-CoV-1 crystal structures. We identified within the active site of the Mpro, in addition to the inhibitory ligands’ interaction with the catalytic C145, two key H-bond interactions with the conserved H163 and E166 residues. Both H-bond interactions are present in almost all co-crystals and are likely to occur also during the viral polypeptide cleavage process as suggested from docking of the Mpro cleavage recognition sequence. We screened in silico a library of 6900 FDA-approved drugs (ChEMBL) and filtered using these key interactions and selected 29 non-covalent compounds predicted to bind to the protease. Additional screen, using DOCKovalent was carried out on DrugBank library (11,414 experimental and approved drugs) and resulted in 6 covalent compounds. The selected compounds from both screens were tested in vitro by a protease activity inhibition assay. Two compounds showed activity at the 50 µM concentration range. Our analysis and findings can facilitate and focus the development of highly potent inhibitors against SARS-CoV-2 infection.

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  1. Version published to 10.1038/s41598-020-77794-5
  2. ScreenIT

    SciScore for 10.1101/2020.09.10.288720: (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
    Preparing a drug library from ChEMBL for non-covalent docking: The ChEMBL database contains 6,900 drugs in various stages of clinical trials.
    ChEMBL
    suggested: (ChEMBL, RRID:SCR_014042)
    Preparing a drug library from DrugBank for covalent docking: We used the DrugBank database44 that includes 11414 preclinical and clinical small molecules.
    DrugBank
    suggested: (DrugBank, RRID:SCR_002700)
    In addition, we favored compounds that did not violate the two hydrophobic regions within the binding site as calculated by Maestro’s SiteMap tool (Schrödinger Release 2020-1: SiteMap, Schrödinger, LLC, New York, NY, 2020.41,42)
    Maestro’s
    suggested: None
    SiteMap
    suggested: (Biositemaps, RRID:SCR_001976)

    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 10.1101/2020.09.10.288720v1 on bioRxiv