Recent studies have established the role of bacteria including Streptococcus pneumoniae, Helicobacter pylori, Chlamydia pneumonia, Mycobacterium tuberculosis, and Porphyromonas gingivalis in the development of atherosclerosis. These bacteria contribute to plaque formation via promoting Th1 immune responses and speeding up ox-LDL formation. Hence, we employed computational reverse vaccinology (RV) approaches to deviate immune response toward Th2 via engineering a novel immunogenic chimera protein. Prominent atherogenic antigens from related bacteria were identified. Then, machine learning-based servers were employed for predicting CTL and HTL epitopes. We selected epitopes from a wide variety of HLAs. Then, a chimeric protein sequence containing TAT peptide, adjuvant, IL-10 inducer, and linker-separated epitopes was designed. The conformational structure of the vaccine was built via multiple-template homology modelling using MODELLER. The initial structure was refined and validated by Ramachandran plot. The vaccine was also docked with TLR4. After that, molecular dynamics (MD) simulation of the docked vaccine-TLR4 was conducted. Finally, the immune simulation of the vaccine was conducted via the C-ImmSim server. A chimera protein with 629 amino acids was built and, classified as a non-allergenic probable antigen. An improved ERRAT score of 80.95 for the refined structure verified its stability. Additionally, validation via the Ramachandran plot showed 98.09% of the residues were located in the most favorable and permitted regions. MD simulations showed the vaccine-TLR4 complex reached a stable conformation. Also, RMS fluctuations analysis revealed no sign of protein denaturation or unfolding. Finally, immune response simulations indicated a promising response by innate and adaptive immunity. In summary, we built an immunogenic vaccine against atherosclerosis and demonstrated its favorable properties via advanced Immunoinformatics analyses. This study may pave the path for combat against atherosclerosis.
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