EP9158H: An Immunoinformatics-Designed mRNA Vaccine Encoding Multi-Epitope Antigens and Dual TLR Agonists for Tuberculosis Prevention.

Background: Tuberculosis (TB) remains a pressing global health crisis. The inadequate efficacy of the BCG vaccine against adult pulmonary TB underscores the urgent need for novel, effective vaccines. This study aimed to design a novel mRNA vaccine candidate against TB using a rational immunoinformatics approach. Methods: From 13 antigens, >12,000 epitopes were filtered to select 60 optimal peptides (36 CTL, 16 HTL, 8 B-cell), assembled into 25 scaffolds with 49 TLR2/4 agonist configurations. EP9158H underwent structural modeling, 100 ns molecular dynamics, docking, immune simulation, RNAfold, and conservation analysis across 76 strains. Results: EP9158H, encoding 15 CTL, 9 HTL, and 8 B-cell epitopes flanked by TLR2 agonist ESAT-6 and TLR4 agonist HBHA, emerged as the optimal candidate. All 32 constituent epitopes showed >81% conservation, with 81.25% exhibiting perfect identity across MTBC lineages. The scaffold demonstrated high solubility (0.531), broad population coverage (73.76% MHC-I, 88.91% MHC-II), optimal TLR2/4 docking scores (-1359.7 and -1348.3), and robust structural stability (ProSA Z-score -6.18; RMSD 22-27 Å). Immune simulation predicted strong Th1-biased T-cell responses and high levels of antibody titers. RNAfold analysis revealed stable mRNA secondary structures (MFE -1127.5 kcal/mol) supporting efficient translation. Conclusions: EP9158H integrates broad epitope coverage, dual TLR agonism, and validated stability. Compared to single-antigen vaccines, it offers superior strain coverage, enhanced innate activation, and mRNA advantages for CTL induction, warranting experimental validation.