A novel conformational state for SARS-CoV-2 main protease

  1. Emanuele Fornasier
  2. Maria Ludovica Macchia
  3. Gabriele Giachin
  4. Alice Sosic
  5. Matteo Pavan
  6. Mattia Sturlese
  7. Cristiano Salata
  8. Stefano Moro
  9. Barbara Gatto
  10. Massimo Bellanda
  11. Roberto Battistutta

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Abstract

The SARS-CoV-2 main protease (M pro ) has a pivotal role in mediating viral genome replication and transcription of coronavirus, making it a promising target for drugs against Covid-19 pandemic. Here we present a crystal structure of M pro disclosing new structural features of key regions of the enzyme. We show that the oxyanion loop, involved in substrate recognition and enzymatic activity, can adopt a new conformation, which is stable and significantly different from the known ones. In this new state the S1 subsite of the substrate binding region is completely reshaped and a new cavity near the S2’ subsite is created. This new structural information expands the knowledge of the conformational space available to M pro , paving the way for the design of novel classes of inhibitors specifically designed to target this unprecedented binding site conformation, thus enlarging the chemical space for urgent antiviral drugs against Covid-19 pandemic.

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    SciScore for 10.1101/2021.03.04.433882: (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
    The final structures were obtained by alternating cycles of manual refinement with Coot (Emsley and Cowtan, 2004) and automatic refinement with phenix.refine (Afonine et al., 2012).
    Coot
    suggested: (Coot, RRID:SCR_014222)
    At the end, the model was submitted to ensamble.refinement (Burnley et al., 2012) by Phenix with default parameters.
    Phenix
    suggested: (Phenix, RRID:SCR_014224)
    Molecular Dynamics simulations were then performed using ACEMD3 (Harvey et al., 2009) software, which is based upon OpenMM 7.4.2 (Eastman et al., 2017) engine.
    OpenMM
    suggested: (OpenMM, RRID:SCR_000436)
    The collected data was then plotted making use of the Matplotlib (Hunter, 2007
    Matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)
    ) Python library.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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: 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.

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  2. Version published to 10.1101/2021.03.04.433882v1 on bioRxiv