Designing an Efficient Multi-epitopeVaccine against Acinetobacter baumanniiusing Immunoinformatics Approaches

Background and Objectives: Acinetobacter baumannii (A. baumannii) is an emerging multi-drug resistant pathogen causing significant mortality inhospitalized ICU patients. The emergence of antibiotic resistance has increased mortality and costs of treatment. The design of a vaccine against A. baumannii would have a great beneficial impact on public health. Materials and Methods: Three known antigenic proteins from A. baumannii ( OmpA,Phospholipase D and Bap ) were analyzed for the prediction of immunogenic B cell and Tcell epitopes, using online algorithms. Based on in silico analysis, epitope-rich domains including highly scored T cell and B cell epitope were selected and designed protein validated using the ProSA-web, Molprobity and the Ramachandran plot. The obtained highquality model was applied for conformational B-cell epitopes selection and docking analyses with toll like receptor 4 (TLR4). The affinity and the map of interactions between the receptor (TLR4) and recombinant protein were investigated via docking protocols. Result: Molecular dynamic studies demonstrated that the recombinant protein-TLR4 docked model was stable during simulation time. We believe that our vaccine candidate is able to induce IgG antibodies, and Th1/Th17-mediated protective immunity that are crucial for eradicating A. baumannii infection. Conclusion: The in silico analysis showed that the designed recombinant protein ( OmpA,Phospholipase D and Bap ) could be considered as apromising vaccine candidate against A. baumannii.