In-silico design of a novel multi-epitope vaccine against Chapare virus using integrated immunoinformatics and bioinformatics approaches

Chapare mammarinavirus, is a pathogen belonging to the Arenaviridae family and is responsible for causing Chapare hemorrhagic fever in humans. No vaccines or antiviral drugs are currently available for CHAPV . Using immunoinformatics algorithm, we identified potential CTL, B-cell, and HTL epitopes from the virus’s glycoprotein precursor, nucleocapsid protein, and Z protein precursor to develop a vaccine candidate. Several linkers, including KK, GPGPG, and AAY were used to connect these epitopes. In addition, the adjuvant 50 S ribosomal protein L7/L12 was linked to the C-terminal end of the vaccine using an EAAAK linker. Furthermore, the three dimensional structure of the designed multi-epitope subunit vaccine was validated through ERRAT, PROCHECK, and ProSA-web servers. As a result, the ERRAT value of the vaccine was recorded as 88.167, the Ramachandran plot showed that 88.8% of residues were located in the most favored region, while the vaccine showed a Z-score of −7.56. In addition, we predict a vaccine antigenicity score of 0.953767, and immunogenicity score of −6.88914. The validated structure was docked with TLR7 and showed stability in MD simulations. Codon optimization revealed a CAI value of 0.93, and a GC content at 50.30% for the vaccine construct, with the pET28a (+) vector indicating proper expression. Immune simulations demonstrated enhanced TC and TH cells, high levels of IgM + IgG and IgG1 + IgG2, and a range of cytokines, suggesting a strong immune response and rapid antigen elimination. This research lays the groundwork for future experimental evaluations to verify the vaccine’s safety and immunogenicity, offering a potential therapeutic strategy against CHAPV -related conditions.