Comput Struct Biotechnol J
. 2021 Jul 2.
doi: 10.1016/j.csbj.2021.06.041. Online ahead of print.
Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses
Christopher A Beaudoin 1 , Arian R Jamasb 1 2 , Ali F Alsulami 1 , Liviu Copoiu 1 , Andries J van Tonder 3 , Sharif Hala 4 5 , Bridget P Bannerman 1 , Sherine E Thomas 1 , Sundeep Chaitanya Vedithi 1 , Pedro H M Torres 6 , Tom L Blundell 1
Affiliations
- PMID: 34234921
- PMCID: PMC8249111
- DOI: 10.1016/j.csbj.2021.06.041
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: COVID-19; Coronavirus spike protein; Infectious disease; MERS-CoV; SARS-CoV; SARS-CoV-2; Structural bioinformatics; Viral host mimicry.