AUTHOR=Cicaloni Vittoria , Costanti Filippo , Pasqui Arianna , Bianchini Monica , Niccolai Neri , Bongini Pietro 

TITLE=A Bioinformatics Approach to Investigate Structural and Non-Structural Proteins in Human Coronaviruses

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.891418

DOI=10.3389/fgene.2022.891418

ISSN=1664-8021

ABSTRACT=Recent studies confirmed that people unexposed to SARS-CoV2 have preexisting reactivity, probably due to previous exposure to widely circulating common cold coronaviruses. Such preexistent reactivity against SARS-CoV2 comes from memory T cells able to specifically recognize a SARS-CoV2 epitope of structural and non-structural proteins as well as the homologous epitopes from common cold coronaviruses. Therefore, it is important to understand the SARS-CoV2 cross-reactivity by investigating these protein sequence similarities with different circulating coronaviruses. Additionally, the emerging SARS-CoV2 variants lead to an intense interest in whether mutations in proteins (especially in the spike) could potentially compromise vaccine effectiveness. Since it is not clear that the differences in clinical outcomes are caused by common cold coronaviruses, a deeper investigation on cross-reactive T cell immunity to SARS-CoV2 is crucial to examine the differential COVID-19 symptoms and vaccines performance. Therefore, the present study can be a starting point for further research on cross-reactive T cell recognition between circulating common cold coronaviruses and SARS-CoV2, including the most recent variants Delta and Omicron. In the end, a deep learning approach, based on Siamese networks, is proposed, to accurately and efficiently calculate a BLAST-like similarity score between protein sequences.