In-silico Immunomodelling of 2019-nCoV

Abstract Background: Novel Corona Virus 2019 (2019-nCoV) is a positive-sense single-strand RNA virus form coronaviridae family, responsible for corona virus infectious disease 2019 (COVID-19) with rapid transmission. The aim of this study is characterization of major viral proteins, prediction of antigen proteasomal cleavage pattern, MHC class I processing and presentation, B- and T-cell epitopes, and anti-inflammatory epitopes of 2019-nCoV, compared with SARS-CoV. Methods: The aminoacid sequence of spike surface (S) glycoprotein, membrane (M) glycoprotein, envelop (E) protein and nucleocapsid (N) phosphoprotein were obtained from NCBI. The sequences were aligned by MEGA 7.0 and modeled by SWISS-MODEL. The proteasomal cleavage pattern, MHC class I processing and T-cells epitopes were predicted via IEDB analysis and EPISOFT. The B-cell epitopes were predicted by BepiPred 2.0. Also, prediction of anti-inflammatory epitopes was performed by AntiFlam. Results: Two major antigen proteins, S glycoprotein and M glycoprotein of 2019-nCoV, respectively, have 26.57% and 20.59% less efficiency in proteasomal cleavage and presentation to MHC class I, comparing SARS-CoV. There are less B-cell predicted epitopes in 2019-nCoV, comparing SARS-CoV. The anti-inflammatory properties of 2019-nCoV S glycoprotein and N protein is higher than SARS-CoV. Discussion: It seems that the evolution of 2019-nCoV is on the way of deficiency in antigen presenting to MHC class I and escaping from cellular immunity. Also, the predicted hotspot epitopes potentially can be used to induction of adaptive cellular immunity against 2019-nCoV. In addition, 2019-nCoV appears to be less immunopathogenic than SARS-CoV due to its higher anti-inflammatory proteins.