Computer-aided Rationale Design and Validation of a Multi-epitope Subunit Vaccine Against an Emerging Alongshan virus

Alongshan virus (ALSV) is a tick-borne phlebovirus first identified in China and later reported in Russia, Mongolia, Finland and Germany. Its frequent detection in ticks and domestic animals suggests a broad zoonotic reservoir and a potential risk for wider human transmission. Since most viral infections lack effective drug treatments, vaccination remains a crucial strategy for preventing viral spread. This study aimed to design an in-silico multi-epitope vaccine (MEV) against ALSV using its essential structural proteins (VP1a, VP1b and VP3). Immunoinformatics methods were employed to predict T and B cell antigenic determinants within these proteins, paving the way for a potential ALSV vaccine. The MEV candidate was constructed by linking selected B and T cell epitopes with suitable linkers and incorporating beta-defensin as an adjuvant. Docking simulations with TLR-4 revealed numerous interacting residues, further confirming the vaccine’s potential interaction with the immune system. In-silico cloning using E. coli as the host yielded a favorable codon adaptation index (CAI) value of 0.93, indicating optimal protein expression within this chosen host. Additionally, molecular dynamics simulations of the vaccine-complex during a 150 ns run suggested a stable environment. Analyses like RMSD, radius of gyration and RMSF confirmed minimal changes, primarily in the active site loop region. Moreover, MMGBSA/PBSA calculations yielded high binding affinities (–226.15 and 227.18 kcal/mol), signifying a strong interaction between the vaccine and its target. While this study showcases a promising in-silico vaccine design, experimental validation remains crucial to confirm its efficacy and safety for further development.