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

Authors: Beaudoin, Christopher A; Jamasb, Arian R; Alsulami, Ali F; Copoiu, Liviu; van Tonder, Andries J; Hala, Sharif; Bannerman, Bridget P; +4 Authors

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

Abstract

SummaryViruses 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.HighlightsPotential coronavirus spike protein mimicry revealed by structural comparisonHuman and non-human protein potential interactions with virus identifiedPredicted structural mimicry corroborated by protein-protein dockingEpitope-based alignments may help guide vaccine effortsGraphical abstract

Keywords

Infectious disease, SARS-CoV-2, COVID-19, SARS-CoV, Viral host mimicry, MERS-CoV, Structural bioinformatics, Coronavirus spike protein, TP248.13-248.65, Biotechnology, Research Article

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Top 10%
Top 10%
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