In silico design of a multi-epitope vaccine against tick-borne encephalitis virus via immunoinformatic analysis

Tick-borne encephalitis virus (TBEV) is a serious pathogen that poses a significant threat to humans, causing encephalitis that can result in lifelong sequelae. In this study, we focused on the complete proteomes of the five current TBEV subtypes to identify dominant epitopes. Immunoinformatics tools were employed to screen for LBL, HTL, and CTL epitopes. These epitopes were then linked using various linkers and combined with adjuvants and histidine tag. The vaccine underwent a series of physicochemical property analyses, including secondary structure prediction, three-dimensional structure prediction, molecular docking, molecular dynamics simulation, immune simulation, and in silico cloning. The results indicate that the vaccine is highly conserved, strongly immunogenic, stable, non-allergenic, and non-toxic. Molecular docking and molecular dynamics simulation demonstrate that the vaccine can form a stable binding complex with TLR3. Immune simulation analysis shows that the vaccine effectively stimulates both cellular and humoral immune responses, accompanied by an increase in cytokine titers. Furthermore, through codon optimization and in silico cloning, the vaccine can be stably and effectively expressed in the Escherichia coli system. As an effective candidate for TBEV vaccination, the multi-epitope vaccine developed in this study has promising application prospects and provides a new approach for the research, development, and improvement of vaccines targeting TBEV.