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Searching for safe SARS COV­2 immunodominant peptides in silico

HLA molecules function to control the constancy of the internal environment of the body. HLA class I molecules are expressed on the surface of all nucleated cells and represent the peptides of all proteins that are synthesized in each individual cell. When a cell is infected with a virus, the peptides of its proteins bind to HLA class I and inform the immune system of the presence of the virus in that cell. The SARS COV-2 virus is chosen as a relevant example. This publication discusses an algorithm for selecting immunodominant peptides of SARS COV-2 virus that can be used to determine body immunoreactivity, immunoprophylaxis and immunotherapy. Proteins from the original strain hCoV-19/Wuhan/WIV04/2019 (hereafter WIV04), the isolate MW674675.1. from RB (hereafter MW674675.1.), strain B.1.617.2 from India (hereafter delta or MZ314977.1.), and the worrisome variant B.1.1.529 (hereafter omicron or OL677199.1) were analyzed. Immunodominant peptides from the SARS COV-2 proteome were searched using various programs on open access platforms: NCBI – GenBank, Protein; IEDB – MHC-I Processing Predictions, Population Coverage; GISAID – CoVsurver: Mutation Analysis of hCoV-19, UNIPROT – BLAST; ToxinPred. The search work resulted in the selection of 27 immunodominant peptides – targets for cytotoxic T-lymphocytes by representation through HLA-A *02:01. We hope that this information will contribute to the dissemination and implementation of ideas aimed at the safest prevention of infections. In predicting in silico bases for peptide vaccines, the practical component can be approached in an early and efficient manner, leading to personalized vaccination of humans as an extremely effective measure.