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The development of a vaccine against Helicobacter pylori remains a public health priority due to its role in various gastric and non-gastric diseases, compounded by the rise of antibiotic resistance. To address the urgent need for novel interventions, we designed an in-silico self-amplifying RNA (saRNA)-based multi-epitope peptide vaccine targeting critical stages of H. pylori pathogenesis: gastric acid neutralization, bacterial adhesion, and toxin-mediated tissue damage. We employed a comprehensive computational and immunoinformatics pipeline and tools such as Geptop 2.0, VaxiJen, PSORTb v3.0.2, VirulentPred 2.0, BLASTp, TMHMM, and Expasy, IEDB's NetMHCpan, NetMHCIIpan, AutoDock Vina, GROMACS v2024, PSIPRED, I-TASSER, PROSA-web, ERRAT, ClusPro 2.0, iMODS to identify, prioritize and validate the designed multi-epitope peptide as an effective vaccine candidate. Five essential proteins in different stages (UreB, BabA, HpaA, CagA, and VacA) were selected based on their antigenicity, virulence, conserveness, human non-homologous, and transmembrane helix presence. Helper T-cell (HTL) and cytotoxic T-cell (CTL) epitopes were predicted to ensure broader HLA allele coverage. Predicted epitopes were assessed for immunogenicity, allergenicity, toxicity, and cytokine-inducing potential. The top 10 HTL and 10 CTL epitopes were incorporated into the multi-epitope Hp vaccine which showed strong binding affinities to MHC molecules and stable peptide-MHC interactions by in molecular docking and dynamics simulations. The designed Hp vaccine sequence was incorporated in standard saRNA model where second ORF (ORF-2) encoded the target vaccine peptide. Structural analyses of the translated antigen showed high structural reliability. Molecular docking and dynamic simulation of the Hp vaccine with Toll-like receptor 4 (TLR4) confirmed stable interactions, suggested effective innate immune activation. Finally, population coverage, discontinuous B-cell epitopes and post-translational modifications analysis confirmed immunogenic potential. Despite these promising in-silico findings, challenges remain in translating computational predictions into experimental efficacy, particularly regarding RNA stability, vaccine delivery, and immune response durability. Therefore, further in vitro and in vivo validation is warranted to confirm its efficacy and safety.
Razzak et al. (Tue,) studied this question.