Design and in silico evaluation of PV-GNProtecta: an mRNA multi-epitope vaccine candidate against Puumala virus using immunoinformatics and structural analysis

Abstract Puumala virus (PUUV), the principal causative agent of nephropathia epidemica (NE), poses a significant public health threat due to its zoonotic transmission, renal complications, and the lack of an approved vaccine. In this study, an immunoinformatics-driven mRNA multi-epitope vaccine, PV-GNProtecta, was designed using conserved regions of the viral glycoprotein (G) and nucleoprotein (N). Highly antigenic, non-allergenic, and non-toxic T-cell and B-cell epitopes were identified and assembled with appropriate adjuvants to enhance immunogenicity. Population coverage analysis suggested broad HLA responsiveness across diverse populations. The vaccine construct exhibited favorable physicochemical properties, including stability, solubility, and antigenicity. Structural validation predicted high model quality, with 95.5% of residues located in favored Ramachandran regions and an ERRAT score of 91.4. Molecular docking and MM-GBSA analyses predicted favorable computational interactions between PV-GNProtecta and TLR4, while a 100 ns molecular dynamics simulation provided computational insights into the dynamic behavior of the vaccine-TLR4 complex. Codon optimization suggested compatibility of the designed sequence with an Escherichia coli -based expression framework. Immune simulation predicted potential humoral and cellular immune response patterns, including changes in IgG, IFN-γ, and IL-2 levels. The designed mRNA sequence exhibited favorable predicted secondary structural characteristics; however, further experimental evaluation is required to assess translational efficiency and stability. Although this study is limited to computational analyses and requires experimental validation, the findings suggest that PV-GNProtecta may represent a potential candidate for further investigation against PUUV infection.