Vaccinomics-based identification of immunodominant epitopes in the tick-borne encephalitis virus polyprotein for multi-epitope vaccine development

Tick-borne encephalitis virus (TBEV), a neurotropic flavivirus transmitted primarily by Ixodes ticks, poses a significant threat to public health. Globally, an estimated 10,000 to 15,000 cases of TBEV were reported annually, with variations based on regional outbreaks. The rapid transmission of TBEV and the unavailability of specific antiviral therapies highlight the urgent necessity of developing an effective vaccine to address this significant public health concern. Therefore, in the current study, we selected the TBEV polyprotein to identify immunodominant cytotoxic T-lymphocytes (CTLs), helper T-lymphocytes (HTLs), and B cells epitopes, which could trigger both humoral and cellular immune responses. These epitopes were selected based on high antigenicity, non-allergenicity, non-toxicity, conservation, class-I immunogenicity, and interferon-gamma induction. The chosen epitopes were joined using AAY, GPGPG, and KK linkers, and the 50S ribosomal protein L7/L12 was incorporated as an adjuvant to formulate the multi-epitope vaccine construct. The vaccine construct comprised 750 amino acid residues, encompassing 74.98% of the worldwide population, ensuring broad applicability among various ethnicities. Following molecular docking simulation, the TBEV vaccine model showed high potential, with the lowest binding energy (-1356.0 Kcal/mol) and positive physicochemical and immunological attributes. Immune simulations and dynamic studies verified that the designed vaccine construct is stable and capable of triggering a strong immune reaction in host cells. The anticipated results suggest that the designed vaccine has considerable capacity to provide defense against TBEV. Nevertheless, additional in-vitro and in-vivo studies are advised to thoroughly confirm its safety and effectiveness in fighting this debilitating vector-borne illness. This chart illustrates the overall immunoinformatics-based methodology used to design a multi-epitope vaccine construct targeting polyprotein in tick-borne encephalitis virus, and created with Draw.io ( https://app.diagrams.net/ ), Flaticon ( https://www.flaticon.com/ ), and Smart ( https://smart.servier.com/ ).