Dynamics of the ACE2–SARS-CoV-2/SARS-CoV spike protein interface reveal unique mechanisms

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Abstract

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major public health concern. A handful of static structures now provide molecular insights into how SARS-CoV-2 and SARS-CoV interact with its host target, which is the angiotensin converting enzyme 2 (ACE2). Molecular recognition, binding and function are dynamic processes. To evaluate this, multiple 500 ns or 1 μs all-atom molecular dynamics simulations were performed to better understand the structural stability and interfacial interactions between the receptor binding domain of the spike (S) protein of SARS-CoV-2 and SARS-CoV bound to ACE2. Several contacts were observed to form, break and reform in the interface during the simulations. Our results indicate that SARS-CoV-2 and SARS-CoV utilizes unique strategies to achieve stable binding to ACE2. Several differences were observed between the residues of SARS-CoV-2 and SARS-CoV that consistently interacted with ACE2. Notably, a stable salt bridge between Lys417 of SARS-CoV-2 S protein and Asp30 of ACE2 as well as three stable hydrogen bonds between Tyr449, Gln493 and Gln498 of SARS-CoV-2 and Asp38, Glu35 and Lys353 of ACE2 were observed, which were absent in the ACE2–SARS-CoV interface. Some previously reported residues, which were suggested to enhance the binding affinity of SARS-CoV-2, were not observed to form stable interactions in these simulations. Molecular mechanics-generalized Born surface area based free energy of binding was observed to be higher for SARS-CoV-2 in all simulations. Stable binding to the host receptor is crucial for virus entry. Therefore, special consideration should be given to these stable interactions while designing potential drugs and treatment modalities to target or disrupt this interface.

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  1. SciScore for 10.1101/2020.06.10.143990: (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
    Simulation data was analyzed using packaged and in house scripts and plotted using R 3.6.0 (https://www.r-project.org).
    https://www.r-project.org
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

    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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