Design of a novel multi-epitope-based vaccine against Bundibugyo Ebolavirus using computational approach

Background: Ebola virus (EBOV), a member of the Filoviridae family, is a highly lethal disease that has caused multiple outbreaks primarily in Central Africa. According to the World Health Organization (WHO) report, the Ebola Virus Disease death rate in 2019 was around 67 %. Specifically, Bundibugyo Ebolavirus (BEBOV) has a relatively lower pathogenic mortality rate, estimated at 37 %. Previous epidemics have seen varying death rates ranging from 25 to 95 % due to the lack of effective medicines and immunizations. Objectives: This study aimed to design a multi-epitope vaccine against BEBOV using immunoinformatics to induce robust immune responses. Methods and results: T-cell (CTL and HTL) and linear B-cell epitopes from spike glycoprotein and nucleoprotein were identified and screened for antigenicity (VaxiJen score: 0.6488), allergenicity, and immunogenicity. Selected epitopes were combined into a vaccine construct with beta-defensin as an adjuvant. The vaccine exhibited favorable physicochemical properties and solubility (0.863482). Molecular docking and dynamics simulations revealed strong binding to TLR-3 (docking score: −354.13 kcal/mol). Codon optimization and in silico cloning suggested efficient expression in Escherichia coli. Conclusion and future recommendation: The designed multi-epitope vaccine demonstrates promising immunogenic potential against BEBOV. Experimental validation is required to confirm efficacy and safety, and further studies should focus on optimization and clinical evaluation for potential outbreak prevention.