High-throughput molecular dynamics-based alchemical free energy calculations for predicting the binding free energy change associated with the common mutations in the spike receptor-binding domain of SARS-CoV-2

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Abstract

The ongoing pandemic caused by SARS-CoV-2 has gone through various phases. From the initial outbreak the virus has mutated several times, with some lineages showing even stronger infectivity and faster spread than the original virus. Among all the variants, beta, gamma, delta and the latest (omicron) are currently classified as variants of concern (VOC) while the remaining are labelled either as variants of interest (VOI) or variants under monitoring (VUM). In this work, we have focused on the mutations observed in important variants, particularly at the receptor-binding domain (RBD) of the spike protein that is responsible for the interactions with the host ACE2 receptor and binding of antibodies. Studying these mutations is particularly important for understanding the viral infectivity, spread of the disease and for tracking the escape routes of this virus from antibodies. Molecular dynamics (MD) based alchemical free energy calculations have been shown to be very accurate in predicting the free energy change due to a mutation that could have a deleterious or a stabilising effect on the protein itself or its binding affinity to another protein. Here, we investigated the significance of six commonly observed spike RBD mutations on the stability of the spike protein binding to ACE2 by free energy calculations using high throughput MD simulations. For comparison, we also used other (rigorous and non-rigorous) binding free energy prediction methods and compared our results with the experimental data if available. The alchemical free energy-based method consistently predicted the free-energy changes with an accuracy close to ±1.0 kcal/mol when compared with the available experimental values. As per our simulation data the most significant mutations responsible for stabilising the spike RBD interactions with human ACE2 are N501Y and L452R.

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  1. SciScore for 10.1101/2022.03.07.483402: (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 complex stability upon mutation was predicted by providing the PDB ID of the protein-protein complex (6ZLG) to the webserver (http://cupsat.tu-bs.de/) using the thermal experimental method and selecting one mutation at a time.
    http://cupsat.tu-bs.de/
    suggested: (CUPSAT, RRID:SCR_010773)

    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.
    • 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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