Immunoinformatics based design of a multiepitope vaccine targeting Streptobacillus moniliformis for the prevention of rat-bite fever

Abstract Objectives To design and computationally evaluate a multiepitope-based vaccine candidate targeting antigenic proteins of Streptobacillus moniliformis using immunoinformatics approaches. Methods Three antigenic proteins, ATP-dependent zinc metalloprotease FtsH, signal peptidase I, and protein translocase subunit SecY, were selected based on antigenicity, non-allergenicity, and non-toxicity. B-cell and T-cell epitopes were predicted and screened for immunogenic potential and global population coverage. A multiepitope vaccine construct containing six MHC class I and six MHC class II epitopes was assembled using appropriate linkers and a beta-defensin-3 adjuvant. Structural modeling, molecular docking with Toll-like receptor 4 (TLR4), and molecular dynamics simulations were performed to assess structural behavior and receptor interactions. Codon optimization and in silico cloning were conducted to evaluate expression feasibility. Immune simulations were performed to estimate potential immune responses. Results The final vaccine construct showed antigenicity with a VaxiJen score of 0.5666 and structural stability with an instability index of 32.50. Population coverage analysis indicated 93.20 % global coverage. Molecular docking and molecular dynamics simulations indicated stable interactions with TLR4. Codon optimization suggested improved translational compatibility in Escherichia coli . Immune simulation indicated increased levels of IgG and IgM antibodies and cytokines including IFN gamma and IL-2. Conclusions The computational analysis suggests that the designed multiepitope construct has characteristics associated with immunogenic potential and structural stability. Further experimental validation is required to confirm its biological efficacy.