In silico Design and Analysis of Engineered Proteins Containing Multi-Epitope and Immunodominant Domains Derived From Rickettsia prowazekii Antigens.

Epidemic louse-borne typhus caused by Rickettsia prowazekii and transmitted by the human body louse, remains a major public health threat in many developing regions. Historical records indicate that outbreaks have resulted in up to million cases annually, with mortality ranging from thousands to millions. Early and accurate diagnosis is critical for improving the efficacy of antibiotic therapies. However, existing serological diagnostic methods often suffer from limited sensitivity, specificity, and reliability. In this study, we applied integrated in silico immunoinformatics and structural bioinformatics approaches to identify antigenic targets and to design and characterize engineered proteins for diagnostic applications. Genomic and proteomic analyses identified Sca4 and OmpB as highly antigenic proteins of Rickettsia prowazekii. Computational epitope prediction mapped linear B-cell epitopes within multi-epitope regions of Sca4 and immunodominant regions of OmpB. Two engineered proteins (MA1 and MA2) were computationally designed: MA1 using selected linear B-cell epitopes linked via flexible peptide linkers with a fusion tag, and MA2 using truncated immunodominant domains with a fusion tag. The engineered proteins were computationally evaluated for physicochemical properties, antigenicity, solubility, stability, and sequence homology, and they demonstrated favorable characteristics with minimal similarity to human proteins. Structural modeling, followed by molecular docking and molecular dynamics simulations with the TLR4 receptor, suggested preserved structural integrity and stable protein-receptor interactions. Overall, these in silico findings underscore the potential of MA1 and MA2 constructs as potential diagnostic candidates and provide a basis for further experimental validation, including protein expression and purification, antibody production in animal models, and immunodiagnostic assay development.