Sign in
BioinformaticsbioRxiv
Preprint

SARS-CoV2 spike protein displays biologically significant similarities with paramyxovirus surface proteins; a bioinformatics study

Ehsan AhmadiiD, Mohammad Reza ZabihiiD, Ramin HosseinzadehiD, Farshid NoorbakhshiD

Abstract

Recent emergence of SARS-CoV2 and associated COVID-19 pandemic has posed a great challenge for the scientific community. Understanding various aspects of SARS-CoV2 biology, virulence and pathogenesis as well as determinants of immune response have become a global research priority. In this study, we performed bioinformatic analyses on SAR-CoV2 protein sequences, trying to unravel biologically important similarities between this newly emerged virus with other RNA viruses. Comparing the proteome of SARS-CoV2 with major positive and negative strand ssRNA viruses showed significant homologies between SARS-CoV2 spike protein with pathogenic paramyxovirus fusion proteins. This spike-fusion homology was not limited to SARS-CoV2 and it existed for some other pathogenic coronaviruses; nonetheless, SARS-CoV2 spike-fusion homology was orders of magnitude stronger than homologies observed for other known coronaviruses. Moreover, this homology did not seem to be a consequence of general ssRNA virus phylogenetic relations. We also explored potential immunological significance of this spike-fusion homology. Spike protein epitope analysis using experimentally verified data deposited in Immune Epitope Database (IEDB) revealed that the majority of spikes T cell epitopes as well as many B cell and MHC binding epitopes map within the spike-fusion homology region. Overall, our data indicate that there might be a relation between SARS-CoV2 and paramyxoviruses at the level of their surface proteins and this relation could be of crucial immunological importance.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISForcelloni '21Pacheco-Olv '22Pal '21Ahmed '20Jegouic '20Vashi '20
69% semantic matchBioinformatics
Sergio Forcelloni, Anna Benedetti, Maddalena Dilucca+1 more·Current Genomics·Nov 1, 2021· 16 citations