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

https://doi.org/10.1016/j.csbj.2021.06.041Get rights and content
Under a Creative Commons license
open access

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.

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 and druggability of the virus. Peptide and epitope motifs have been detected on coronavirus spike proteins using sequence homology approaches; however, comparing the three-dimensional shape of the protein has been shown as more informative in predicting mimicry than sequence-based comparisons. 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 protein models with the receptor-binding motifs and verify potential mimicked interactions with protein docking simulations. Both human and non-human proteins were returned for all three receptor-binding motifs. For example, all three were similar to several proteins containing EGF-like domains: some of which are endogenous to humans, such as thrombomodulin, and others exogenous, such as Plasmodium falciparum MSP-1. 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.

Keywords

SARS-CoV-2
SARS-CoV
MERS-CoV
Coronavirus spike protein
COVID-19
Viral host mimicry
Infectious disease
Structural bioinformatics

Cited by (0)