Molecular dynamics simulation study reveals effects of key mutations on spike protein structure in SARS-CoV-2

  1. Jerome Rumdon Lon
  2. Binbin Xi
  3. Bingxu Zhong
  4. Yiyuan Zheng
  5. Zixi Chen
  6. Ruoran Qiu
  7. Siqing Zhang
  8. Pei Guo
  9. Hongli Du

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Abstract

SARS-CoV-2 has been spreading rapidly since 2019 and has produced large-scale mutations in the genomes. The mutation in genes may lead to changes in protein structure, which would have a great impact on the epidemiological characteristics. In this study, we selected the key mutations of SARS-CoV-2 from a real-time monitoring tool, including D614G, A222V, N501Y, T716I, S982A, D1118H of spike (S) protein, and performed molecular dynamics (MD) simulations on single-site mutant D614G, double-site mutant D614G&A222V and penta-site mutant N501Y&D614G&T716I&S982A&D1118H to investigate their effects on protein structure and stability using molecular dynamics (MD) simulations. The results suggested that D614G improved the stability of S protein, while D614G&A222V and N501Y&D614G&T716I&S982A&D1118H showed an increased solvent accessible surface area and they might enhance the ability of protein to react with the outside environment. Our findings could complement the mechanistic link between genotype--phenotype--epidemiological characteristics in the study of SARS-CoV-2. We also found no significant difference between the antigenicity of S protein and the mutants through Ellipro, which may reference for vaccine development and application.

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  1. ScreenIT

    SciScore for 10.1101/2021.02.03.429495: (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
    For each system, the MD simulations were performed using Gromacs 2018.3, and the Gromacs 54A7 force field was selected (Huang et al., 2011).
    Gromacs
    suggested: (GROMACS, RRID:SCR_014565)
    The biological macromolecules presented in this paper were drawn with PyMol V2.3.2, and the statistical charts were drawn with Origin 2018.
    PyMol
    suggested: (PyMOL, RRID:SCR_000305)
    Origin
    suggested: (Origin, RRID:SCR_014212)

    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: We detected the following sentences addressing limitations in the study:
    Limitations of the Study: In this study, we used MD simulation to explore the molecular mechanism by which key mutations in SARS-CoV-2 affect transmission. Due to the fluctuation of molecular simulation calculation, the calculation result is bound to have some residuals. MD provides a unique perspective at the molecular level for relevant studies, and the epidemiological trend is consistent with the results of MD. However, the simulation results can only be more accurate after the verification of relevant experiments. Computers cannot fully simulate the movement of real proteins, which is the limitation of this project. Resource Availability: Data and Code Availability: Raw data tables for RMSD, RMSF, RG, SASA, H-Bond, and Antigenicity are provided in the supplementary information. The simulation data is stored in the HPC hardware housed at the Tianhe-2 and can be shared with the corresponding author on request.

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.02.03.429495 on bioRxiv