Design of a multi-epitope vaccine candidate against Helicobacter pylori in gastric cancer: an immunoinformatic approach.

Background: Gastric cancer and peptic ulcers can both be caused by Helicobacter pylori (H. pylori). The complexity of such a bacterium has made it difficult to develop an effective treatment. Thus, a computational approach to developing antigenicity, stability, and safety in vaccines against this pathogen will aid in the management of related diseases.

Methods: This investigation chose two H. pylori proteins, SabA and BabA, as epitope prediction targets, and an immunoinformatics platform was used to create a subunit vaccine against H. pylori. The best helper T-lymphocyte (HTLs) along with cytotoxic T-lymphocyte (CTLs) epitopes were chosen according to antigenicity, toxicity and allergenicity. The chosen epitopes, suitable linkers, and adjuvants were combined for creating a final vaccine design. The antigenicity, allergenicity, and physicochemical traits of the vaccine were assessed.

Results: The 3D structure of the multi-epitope vaccine was successfully predicted. The results of molecular docking analysis along with molecular dynamics (MD) simulation on the multi-epitope vaccine and immune receptors complex showed the structure has appropriate interaction energy between its two components and good stability. The vaccine candidate was cloned in silico in the pET28a (+) vector successfully in a suitable site.

Conclusion: The results showed that final vaccine design would work well as an effective prophylactic vaccine against H. pylori. To evaluate vaccine efficacy against the aforementioned bacteria, in vivo and in vitro trials are required.