Sequence characterization and molecular modeling of clinically relevant variants of the SARS-CoV-2 main protease

  1. Thomas J. Cross
  2. Gemma R. Takahashi
  3. Elizabeth M. Diessner
  4. Marquise G. Crosby
  5. Vesta Farahmand
  6. Shannon Zhuang
  7. Carter T. Butts
  8. Rachel W. Martin

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Abstract

The SARS-CoV-2 main protease (M pro ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant selection pressure, with new M pro mutations arising over time. Identification and structural characterization of M pro variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine M pro variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.15.097493: (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
    Open reading frames in these high-quality full genomes were compared with a reference Mpro nucleotide sequence (WT, RefSeq: NC 045512.2, loc: 10,055–10,972), to extract Mpro sequences of at least 80% similarity using a script written in Python v3.7.0 (35).
    Python
    suggested: (IPython, RRID:SCR_001658)
    Full genome alignments were performed using MUSCLE (14) on the complete set of non-synonymous Mpro mutants as well as reference WT, bat, and pangolin sequences.
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    Trees were generated in MEGA X (15), using the Neighbor-Joining method (37); a bootstrap test (38) of 1000 replicates was performed, and distances were calculated using the Maximum Composite Likelihood model (38).
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    Initial variant protein structures were predicted using MODELLER 9.23 (30), using the 6Y2E structure as a template; three rounds of annealing and MD refinement were performed using the “slow” optimization level for each.
    MODELLER
    suggested: (MODELLER, RRID:SCR_008395)
    Table of Contents:
    Contents
    suggested: None

    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.

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  2. Version published to 10.1101/2020.05.15.097493v1 on bioRxiv