Exploring the genomic and proteomic variations of SARS-CoV-2 spike glycoprotein: a computational biology approach

  1. Syed Mohammad Lokman
  2. Md. Rasheduzzaman
  3. Asma Salauddin
  4. Rocktim Barua
  5. Afsana Yeasmin Tanzina
  6. Meheadi Hasan Rumi
  7. Md. Imran Hossain
  8. Amam Zonaed Siddiki
  9. Adnan Mannan
  10. Md. Mahbub Hasan

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Abstract

The newly identified SARS-CoV-2 has now been reported from around 183 countries with more than a million confirmed human cases including more than 68000 deaths. The genomes of SARS-COV-2 strains isolated from different parts of the world are now available and the unique features of constituent genes and proteins have gotten substantial attention recently. Spike glycoprotein is widely considered as a possible target to be explored because of its role during the entry of coronaviruses into host cells. We analyzed 320 whole-genome sequences and 320 spike protein sequences of SARS-CoV-2 using multiple sequence alignment tools. In this study, 483 unique variations have been identified among the genomes including 25 non-synonymous mutations and one deletion in the spike protein of SARS-CoV-2. Among the 26 variations detected, 12 variations were located at the N-terminal domain and 6 variations at the receptor-binding domain (RBD) which might alter the interaction with receptor molecules. In addition, 22 amino acid insertions were identified in the spike protein of SARS-CoV-2 in comparison with that of SARS-CoV. Phylogenetic analyses of spike protein revealed that Bat coronavirus have a close evolutionary relationship with circulating SARS-CoV-2. The genetic variation analysis data presented in this study can help a better understanding of SARS-CoV-2 pathogenesis. Based on our findings, potential inhibitors can be designed and tested targeting these proposed sites of variation.

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    SciScore for 10.1101/2020.04.07.030924: (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 multiple sequence alignment (MSA), Genome Detective Coronavirus Typing Tool uses a reference dataset of 431 whole genome sequences (WGS) where 386 WGS were from known nine coronavirus species.
    WGS
    suggested: None
    The dataset was then aligned with MUSCLE [24].
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    Entropy (H(x)) plot of nucleotide variations in SARS-CoV-2 genome was constructed using BioEdit [25].
    BioEdit
    suggested: (BioEdit, RRID:SCR_007361)
    MEGA X (version 10.1.7) was used to construct the MSAs and the phylogenetic tree using pairwise alignment and neighbor-joining methods in ClustalW [26,27].
    ClustalW
    suggested: (ClustalW, RRID:SCR_017277)
    The overall quality of models was assessed in RAMPAGE server [31] by generating Ramachandran plots (Supplementary Table 1).
    RAMPAGE
    suggested: (RAMPAGE, RRID:SCR_017590)
    PyMol and BIOVIA Discovery Studio were used for structure visualization and superpose [32,33].
    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04321096Active, not recruitingThe Impact of Camostat Mesilate on COVID-19 Infection

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on pages 26, 22 and 23. 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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.04.07.030924 on bioRxiv