Structural Differences In 3C-like protease (Mpro) From SARS-CoV and SARS-CoV-2: Molecular Insights For Drug Repurposing Against COVID-19 Revealed by Molecular Dynamics Simulations

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Abstract

A recent fatal outbreak of novel coronavirus SARS-CoV-2, identified preliminary as a causative agent for series of unusual pneumonia cases in Wuhan city, China has infected more than 20 million individuals with more than 4 million mortalities. Since, the infection crossed geographical barriers, the WHO permanently named the causing disease as COVID-2019 by declaring it a pandemic situation. SARS-CoV-2 is an enveloped single-stranded RNA virus causing a wide range of pathological conditions from common cold symptoms to pneumonia and fatal severe respiratory syndrome. Genome sequencing of SARS-CoV-2 has revealed 96% identity to the bat coronavirus and 79.6% sequence identity to the previous SARS-CoV. The main protease (known as 3C-like proteinase/ Mpro) plays a vital role during the infection with the processing of replicase polyprotein thus offering an attractive target for therapeutic interventions. SARS-CoV and SARS-CoV-2 Mpro shares 97% sequence identity, with 12 variable residues but none of them present in the catalytic and substrate binding site. With the high level of sequence and structural similarity and absence of any drug/vaccine against SARS-CoV-2, drug repurposing against Mpro is an effective strategy to combat COVID-19. Here, we report a detailed comparison of SARS-CoV-2 Mpro with SARS-CoV Mpro using molecular dynamics simulations to assess the impact of 12 divergent residues on the molecular microenvironment of Mpro. A structural comparison and analysis is made on how these variable residues affects the intra-molecular interactions between key residues in the monomer and biologically active dimer form of Mpro. The present MD simulations study concluded the change in microenvironment of active-site residues at the entrance (T25, T26, M49 and Q189), near the catalytic region (F140, H163, H164, M165 and H172) and other residues in substrate binding site (V35T, N65S, K88R and N180K) due to 12 mutation incorporated in the SARS-CoV-2 Mpro. It is also evident that SARS-CoV-2 dimer is more stable and less flexible state compared to monomer which may be due to these variable residues, mainly F140, E166 and H172 which are involved in dimerization. This also warrants a need for inhibitor design considering the more stable dimer form. The mutation accumulated in SARS-CoV-2 Mpro indirectly reconfigures the key molecular networks around the active site conferring a potential change in SARS-CoV-2, thus posing a challenge in drug repurposing SARS drugs for COVID-19. The new networks and changes in microenvironment identified by our work might guide attempts needed for repurposing and identification of new Mpro inhibitors.

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  1. SciScore for 10.1101/2021.08.11.455903: (What is this?)

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

    Table 1: Rigor

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    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The SARS-CoV-2 was also checked individually with other Mpro sequences using BLAST to identify pair-wise sequence identity.
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    Multiple sequence alignment was performed using ClustalW to identify conserved residues followed by ESPript3 for structure-based sequence alignment using SARS-CoV-2 structure as a reference.
    ClustalW
    suggested: (ClustalW, RRID:SCR_017277)
    Physicochemical parameters of all CoV 3CLpro including isoelectric point, instability index, grand average of hydropathicity (GRAVY), and amino acid composition were computed using the ProtParam tool of ExPASy.
    ProtParam
    suggested: (ProtParam Tool, RRID:SCR_018087)
    ExPASy
    suggested: None
    PyMOL, Chimera and other tools were used for in-depth analysis of structural features in SARS-CoV-2 Mpro and differences with other CoV Mpro.
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 30. 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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


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