Immunoinformatic-driven design of a multi-epitope vaccine against Helicobacter pylori

Helicobacter pylori (H. pylori) is present in the gastric mucosa of approximately half of the global population and is classified as a definitive type I carcinogen. Developing a logical and effective vaccine against H. pylori remains a critical need. To enhance immune protection, a multi-epitope vaccine was designed using an immunoinformatic-driven approach. The genome of the pathogen was analyzed to identify potential epitopes using several algorithms for predicting T-cell and B-cell epitopes. The resulting multi-epitope vaccine was evaluated for antigenicity, allergenicity, and physicochemical properties. The tertiary structure was predicted and validated using a Ramachandran plot. Molecular docking analysis revealed favorable interactions between the vaccine and immune receptors, while molecular dynamics simulations performed with GROMACS confirmed the stability of these interactions through key dynamic indexes. Additionally, immune simulations, codon optimization, and in silico cloning were conducted to further evaluate the vaccine candidate. In silico predictions indicate that the proposed vaccine construct may be safe and stable, holding promise as an effective measure against H. pylori-induced gastric inflammation.