An in-silico study of the mutation-associated effects on the spike protein of SARS-CoV-2, Omicron variant

  1. Tushar Ahmed Shishir
  2. Taslimun Jannat
  3. Iftekhar Bin Naser

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Abstract

The emergence of Omicron (B.1.1.529), a new Variant of Concern in the COVID-19 pandemic, while accompanied by the ongoing Delta variant infection, has once again fueled fears of a new infection wave and global health concern. In the Omicron variant, the receptor-binding domain (RBD) of its spike glycoprotein is heavily mutated, a feature critical for the transmission rate of the virus by interacting with hACE2. In this study, we used a combination of conventional and advanced neural network-based in silico approaches to predict how these mutations would affect the spike protein. The results demonstrated a decrease in the electrostatic potentials of residues corresponding to receptor recognition sites, an increase in the alkalinity of the protein, a change in hydrophobicity, variations in functional residues, and an increase in the percentage of alpha-helix structure. Moreover, several mutations were found to modulate the immunologic properties of the potential epitopes predicted from the spike protein. Our next step was to predict the structural changes of the spike and their effect on its interaction with the hACE2. The results revealed that the RBD of the Omicron variant had a higher affinity than the reference. Moreover, all-atom molecular dynamics simulations concluded that the RBD of the Omicron variant exhibits a more dispersed interaction network since mutations resulted in an increased number of hydrophobic interactions and hydrogen bonds with hACE2.

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  1. Version published to 10.1371/journal.pone.0266844
  2. ScreenIT

    SciScore for 10.1101/2022.02.21.481269: (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 Omicron genome sequence was then annotated using the Cov-Seq program, followed by translation using the EMBOSS transeq tool (Liu et al., 2020)(Rice et al., 2000).
    Cov-Seq
    suggested: None
    A pairwise alignment of spike protein sequences was later performed with Clustal Omega, followed by the analysis of mutations (Sievers and Higgins, 2018).
    Clustal Omega
    suggested: (Clustal Omega, RRID:SCR_001591)
    The amino acid composition, molecular weight, distribution of charged residues, hydropathicity, aliphatic index, instability index, and a few other parameters are calculated mainly using the online server EMBOSS Pepstats
    EMBOSS
    suggested: (EMBOSS, RRID:SCR_008493)
    Further verification of the results from Pepstats was conducted using ProtParam, Prosite and AA-prop (Artimo et al., 2012; Bonnal et al., 2012).
    ProtParam
    suggested: (ProtParam Tool, RRID:SCR_018087)
    Prosite
    suggested: (PROSITE, RRID:SCR_003457)
    In addition, several tools, including SNAP2,
    SNAP2
    suggested: None
    , PROVEAN and SIFT, were used to assess the impact of mutations on function (Sim et al., 2012; Choi and Chan, 2015).
    PROVEAN
    suggested: (PROVEAN, RRID:SCR_002182)
    SIFT
    suggested: (SIFT, RRID:SCR_012813)
    Finally, the Pymol graphical software was utilized for figure generation (DeLano, 2020).
    Pymol
    suggested: (PyMOL, RRID:SCR_000305)
    Finally, the MD simulations of both reference and Omicron variant ACE2-RBD systems were run for 200ns with a time step of 2.0 fs under NPT ensemble using GROMACS 2021.2 software and long-range electrostatic interactions were computed using Particle Mesh Ewald (PME) algorithm.
    GROMACS
    suggested: (GROMACS, RRID:SCR_014565)

    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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  3. Version published to 10.1101/2022.02.21.481269 on bioRxiv