Immunoinformatics Aided Design of Conserved Nucleocapsid Peptides Containing HLA Restricted Epitopes as Potential Vaccine Target Against Hantaan Virus Infection

Abstract

Hantaan virus (HNTV) is the prototypical member of the Hantavirus genus of the Hantaviridae family (order of Bunyaviridae), transmitted to humans from rodents such as mice and rats, and is the causative agent of fatal hemorrhagic fever with fatal renal syndrome (HFRS). Case fatality rates range roughly from 5.0% to 15.0%, and several outbreaks have occurred on different continents. HFRS is epidemic primarily in Asia and Europe. About 100,000 cases of HFRS are reported each year, mostly in China, Korea, and Russia. Among them, China is the most affected country, accounting for about 90% or more of HFRS cases worldwide over the past decades. Using different immunoinformatics tools, three conserved peptides (P-1, P-2, and P-3) comprising of several CD8+ and CD4+ T cell epitopes were selected. P-1, P-2 and P-3 peptides were predicted to bind to 676, 1437 and 1202 HLA alleles, respectively. Root mean square deviation (RMSD) values acquired by molecular docking (CABS-Dock) of identified epitopes with 20 HLA alleles (10 each of HLA classes I and II) were found to be comparable with native peptides (peptides bound to HLA in PDB), thereby depicting the good binding interaction of epitopes with HLA molecules. Further, an immunogenic peptide construct was designed by linking peptides and docked with TLR4 receptor. This study is implemented to design a multi-epitope based peptide vaccine against Hantaan virus using its nucleocapsid (N) protein. Various immunoinformatics analyses are considered to support the potential of obtained peptides as vaccine candidates.