Computational Approach for Screening the Whole Proteome of Hantavirus and Designing a Multi-Epitope Subunit Vaccine

Abstract

Hantaviruses are a newly zoonotic emerging group of rodent-borne viruses that have a significant impact on global public health by increasing amplitude and magnitude of outbreaks. As no permanent cure yet, it is now growing and challenging interest to develop a vaccine against Hantavirus. This study endeavored to design a robust subunit vaccine using a novel immunoinformatics approach. After meticulous evaluation, top ones from predicted CTL, HTL, and B-cell epitopes were considered as potential vaccine candidates. Among generated four vaccine models with different adjuvant, the model with TLR-4 agonist adjuvant was selected for its high antigenicity, non-allergenicity, and structural quality. The conformational B-cell epitope prediction assured its humoral response inducing ability. Thereafter, the molecular docking and dynamics simulation confirmed a good binding affinity with immune receptor TLR-4 and stability of the vaccine-receptor complex. In immune simulation, significantly high levels of IgM and IgG1 immunoglobulins, TC and TH-cell populations, and various cytokines (i.e. IFN-{gamma}, IL-2 etc.) are coherence with actual immune response and also showed faster antigen clearance for repeated exposures. Finally, disulfide engineering enhanced vaccine stability and in silico cloning confirmed the better expression in E. coli K12. Nonetheless, experimental validation can proof the proposed vaccines safety and ability to control Hantavirus infection.