In silico prediction of cytotoxic T-cell epitopes from Helicobacter pylori virulence factors using an immunoinformatics approach.

Abstract

Background: Helicobacter pylori infects approximately half of the global population, leading to gastric and duodenal ulcers. Despite the availability of antibiotics, challenges such as patient reluctance, high treatment costs, and antibiotic resistance limit their effectiveness, making vaccination a promising alternative. This study used immunoinformatics to identify candidate epitopes for a multiepitope vaccine construct against H. pylori.

Materials and methods: The protein variability server was utilized for conservation analysis. The epitopes were screened for antigenicity, allergenicity, toxicity, cross-reactivity, and population coverage. Selected epitopes were docked with their corresponding human leukocyte antigen (HLA) alleles, and thermodynamic quantities were determined. Five virulence factors - HopZ, SabA, HP-NAP, OipA, and urease - were selected for their critical roles in bacterial adhesion, immune modulation, and stress survival.

Results: Conservation analysis revealed a highly conserved protein sequence (Shannon index ≤ 0.1). The predicted epitopes had an IC₅₀ value of ≤ 500 nM, indicating strong binding to the corresponding HLAs, with an estimated population coverage of more than 90% in the Southeast Asian region. The predicted epitopes were identified as probable nonallergens, nontoxic, and noncross-reactive (E value >1.0). Molecular docking analysis showed that the candidate epitopes could bind strongly and spontaneously with their corresponding HLA proteins, as evidenced by low negative Gibbs free energy (ΔG) values and dissociation constants (K _D < 100 nM).

Conclusion: The epitopes predicted from the five virulence factors present promising candidates for future H. pylori vaccine design. Further in vitro and in vivo experiments are recommended to validate these preliminary findings.