IMMUNINFORMATICS STUDY IN PREDICTING CYTOTOXIC T LYMPHOCYTE (CTL) EPITOPES OF SARS-COV-2 NUCLOECAPSID PROTEIN

Abstract

Vaccines are one solution to eradicate the Covid-19 pandemic. The best protein for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) to be used as a source for developing an epitope-based Covid-19 vaccine is the nucleocapsid protein. This is because the nucleocapsid protein has a high level of immunogenicity and has an important role in the SARS-CoV-2 virus. an epitope-based vaccines are minimal antigen vaccines that induced the immune system. This study aims to predict the sequence of epitope with HLA in Indonesia (HLA-A*02:01, HLA-A*11:01, and HLA-B*40:01), predict the level of allergenicity using AllerTOP server, toxicity using ToxinPred server, and autoimmunity using IEDB server. The predicted of epitope was carried out by the homology modelling using MODELLER 10.0 and the evaluation using the Ramachandran plot. The results of this study indicate that there are five possible nucleocapsid epitopes as vaccine candidates with non-toxin, non-allergenic, and conservative epitope results with percent identity >90% in Indoensia. The epitope structure has an evaluation of >90% amino acid residues on the Ramachandran plot, so the model can be said to be good based on the plot. We hope that these epitopes can be used in the future for the development of epitope-based vaccines.