A Computational Vaccine Designing Approach for MERS-CoV Infections

Ibrahim, Hiba Siddig; Kafi, Shamsoun Khamis

The aim of this study was to use IEDB software to predict the suitable MERS-CoV epitope vaccine against the most known world population alleles through four selecting proteins such as S glycoprotein and envelope protein and their modification sequences after the pandemic spread of MERS-CoV in 2012. IEDB services is one of the computational methods; the output of this study showed that S glycoprotein, envelope (E) protein, and S and E protein modified sequences of MERS-CoV might be considered as a protective immunogenic with high conservancy because they can elect both neutralizing antibodies and T-cell responses when reacting with B-cell, T-helper cell, and cytotoxic T lymphocyte. NetCTL, NetChop, and MHC-NP were used to confirm our results. Population coverage analysis showed that the putative helper T-cell epitopes and CTL epitopes could cover most of the world population in more than 60 geographical regions. According to AllerHunter results, all those selected different protein showed non-allergen; this finding makes this computational vaccine study more desirable for vaccine synthesis.