Identification of Unique Peptides for SARS-CoV-2 Diagnostics and Vaccine Development by an In Silico Proteomics Approach

Abstract

Ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus strains is posing new COVID-19 diagnosis and treatment challenges. To help efforts to meet these challenges we examined data acquired from proteomic analyses of human SARS-CoV-2-infected cell lines and samples from COVID-19 patients. Initially, 129 unique peptides were identified, which were rigorously evaluated for repeats, disorders, polymorphisms, antigenicity, immunogenicity, toxicity, allergens, sequence similarity to human proteins, and contributions from other potential cross-reacting pathogenic species or the human saliva microbiome. We also screened SARS-CoV-2-infected NBHE and A549 cell lines for presence of antigenic peptides, and identified paratope peptides from crystal structures of SARS-CoV-2 antigen-antibody complexes. We then selected four antigen peptides for docking with known viral unbound T-cell receptor (TCR), class I and II peptide major histocompatibility complex (pMHC), and identified paratope sequences. We also tested the paratope binding affinity of SARS-CoV T- and B-cell peptides that had been previously experimentally validated. The resultant antigenic peptides have high potential for generating SARS-CoV-2-specific antibodies, and the paratope peptides can be directly used to develop a COVID-19 diagnostics assay. The presented genomics and proteomics-based in-silico approaches have apparent utility for identifying new diagnostic peptides that could be used to fight SARS-CoV-2.

Keywords

SARS-CoV-2; COVID-19 vaccines; diagnostic peptides; docking; paratopes; TCR; MHC

Published in

Frontiers in Immunology
2021, Volume: 12, article number: 725240

SLU Authors

• Vetukuri, Ramesh

  • Department of Plant Breeding, Swedish University of Agricultural Sciences
    

Sustainable Development Goals

SDG3 Good health and well-being


UKÄ Subject classification

Immunology in the medical area


Publication identifier

DOI: https://doi.org/10.3389/fimmu.2021.725240

Permanent link to this page (URI)

https://res.slu.se/id/publ/113620