Molecular dynamics and in silico mutagenesis on the reversible inhibitor-bound SARS-CoV-2 main protease complexes reveal the role of lateral pocket in enhancing the ligand affinity

  1. Ying Li Weng
  2. Shiv Rakesh Naik
  3. Nadia Dingelstad
  4. Miguel R. Lugo
  5. Subha Kalyaanamoorthy
  6. Aravindhan Ganesan

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Abstract

The 2019 novel coronavirus pandemic caused by SARS-CoV-2 remains a serious health threat to humans and there is an urgent need to develop therapeutics against this deadly virus. Recent scientific evidences have suggested that the main protease (M pro ) enzyme in SARS-CoV-2 can be an ideal drug target due to its crucial role in the viral replication and transcription processes. Therefore, there are ongoing research efforts to identify drug candidates against SARS-CoV-2 M pro that resulted in hundreds of X-ray crystal structures of ligand-bound M pro complexes in the Protein Data Bank (PDB) describing the interactions of different fragment chemotypes within different sites of the M pro . In this work, we performed rigorous molecular dynamics (MD) simulation of 62 reversible ligand–M pro complexes in the PDB to gain mechanistic insights about their interactions at the atomic level. Using a total of over 3 µs long MD trajectories, we characterized different pockets in the apo M pro structure, and analyzed the dynamic interactions and binding affinity of ligands within those pockets. Our results identified the key residues that stabilize the ligands in the catalytic sites and other pockets of M pro . Our analyses unraveled the role of a lateral pocket in the catalytic site in M pro that is critical for enhancing the ligand binding to the enzyme. We also highlighted the important contribution from HIS163 in the lateral pocket towards ligand binding and affinity against M pro through computational mutation analyses. Further, we revealed the effects of explicit water molecules and M pro dimerization in the ligand association with the target. Thus, comprehensive molecular-level insights gained from this work can be useful to identify or design potent small molecule inhibitors against SARS-CoV-2 M pro .

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  1. Version published to 10.1038/s41598-021-86471-0
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    SciScore for 10.1101/2020.10.31.363309: (What is this?)

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

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    Table 2: Resources

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    The cpptraj module was employed to select the desired number of snapshots and to generate the related topology files for the free energy calculations; whereas, the interface residues were found using the “InterfaceResidues” Pymol script.
    Pymol
    suggested: (PyMOL, RRID:SCR_000305)

    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 page 45. 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.

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  3. Version published to 10.1101/2020.10.31.363309v1 on bioRxiv