Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses

  1. Christopher A Beaudoin
  2. Arian R Jamasb
  3. Ali F Alsulami
  4. Liviu Copoiu
  5. Andries J van Tonder
  6. Sharif Hala
  7. Bridget P Bannerman
  8. Sherine E Thomas
  9. Sundeep Chaitanya Vedithi
  10. Pedro H M Torres
  11. Tom L Blundell

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Abstract

Viruses often encode proteins that mimic host proteins in order to facilitate infection. Little work has been done to understand the potential mimicry of the SARS-CoV-2, SARS-CoV, and MERS-CoV spike proteins, particularly the receptor-binding motifs, which could be important in determining tropism of the virus. Here, we use structural bioinformatics software to characterize potential mimicry of the three coronavirus spike protein receptor-binding motifs. We utilize sequence-independent alignment tools to compare structurally known or predicted three-dimensional protein models with the receptor-binding motifs and verify potential mimicry with protein docking simulations. Both human and non-human proteins were found to be similar to all three receptor-binding motifs. Similarity to human proteins may reveal which pathways the spike protein is co-opting, while analogous non-human proteins may indicate shared host interaction partners and overlapping antibody cross-reactivity. These findings can help guide experimental efforts to further understand potential interactions between human and coronavirus proteins.

Highlights

  • Potential coronavirus spike protein mimicry revealed by structural comparison

  • Human and non-human protein potential interactions with virus identified

  • Predicted structural mimicry corroborated by protein-protein docking

  • Epitope-based alignments may help guide vaccine efforts

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  1. ScreenIT

    SciScore for 10.1101/2021.04.23.441187: (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
    ProtCHOIR builds homo-oligomeric assemblies by searching for homolog templates on a locally created homo-oligomeric protein database using PSI-BLAST, performing a series of structural analyses on the input protomer structure or sequence using Molprobity, PISA, and GESAMT (all three tools as part of the CCP4 Molecular Graphics package), and comparative homology modelling using MODELLER (version 9.24) with molecular dynamics-level optimization and refinement (Altschul et al., 1997; Chen et al., 2010b; Krissinel, 2012; Krissinel and Henrick, 2007; Šali, 2019; Šali and Blundell, 1993).
    Molprobity
    suggested: (MolProbity, RRID:SCR_014226)
    MODELLER
    suggested: (MODELLER, RRID:SCR_008395)
    No records exist of N-linked or O-linked glycosylation motifs near the three RBMs, which was supported by NetNGlyc 1.0 and NetOGlyc 4.0 predictions (Gupta et al., 2004; Steentoft et al., 2013).
    NetNGlyc
    suggested: (NetNGlyc, RRID:SCR_001570)
    NetOGlyc
    suggested: (NetOGlyc, RRID:SCR_009026)
    The structural alignment model of the ligand and putative receptor are refined with RosettaDock to quantify electrochemical complementarity, which is not included in a strict structural alignment screen (Wang et al., 2007).
    RosettaDock
    suggested: (RosettaDock, RRID:SCR_013393)
    The UniProt accession codes were then compared across tools to identify shared top hits.
    UniProt
    suggested: (UniProtKB, RRID:SCR_004426)
    Annotations informing potential protein-protein interactions were obtained from the PDB, STRING, and UniProt databases (Szklarczyk et al., 2019).
    STRING
    suggested: (STRING, RRID:SCR_005223)
    To gain better insight into the binding strength of the potential RBD-receptor complex interactions, we used the FoldX (version 4.0) AnalyseComplex program, which predicts the interaction energy by finding the difference in stability between the individual unfolded molecules and the overall complex (Schymkowitz et al., 2005).
    FoldX
    suggested: (FoldX, RRID:SCR_008522)
    Protein structural alignments were visualized with PyMOL (version 1.8.4.0) (Stout, 2004).
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)
    The graphical abstract was adapted from the “SARS-CoV-2 Spike Protein Conformations” template on BioRender.
    BioRender
    suggested: (Biorender, RRID:SCR_018361)

    Results from OddPub: Thank you for sharing your code and data.

    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.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2021.04.23.441187 on bioRxiv