Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health challenge due to the limited efficacy of the Bacillus Calmette-Guérin (BCG) vaccine. Using an immunoinformatics-driven strategy, we designed and evaluated three distinct multi-epitope vaccine constructs (MEVCs) derived from PPE68, IrtA, and PE9, which were subsequently developed into an mRNA vaccine construct. T-cell and B-cell epitopes were predicted using IEDB tools and BepiPred-3.0, and the designed constructs were systematically evaluated for antigenicity, allergenicity, toxicity, and physicochemical characteristics. Structural modeling with AlphaFold3, followed by epitope mapping and molecular docking with TLR2 and TLR4/MD-2, identified Pattern 3 (PPE68-IrtA-PE9) as the most promising construct. It exhibited the highest antigenicity score (0.6122), a high abundance of B-cell epitopes (0.865), and demonstrated predicted binding to the TLR4/MD-2 complex (ΔG = - 12.2 kcal/mol), forming 12 hydrogen bonds and engaging both receptor components, as well as to TLR2 (ΔG = - 10.4 kcal/mol) with nine hydrogen bonds. In silico immune simulations of Pattern 3 predicted strong T-cell responses, elevated IFN-γ levels, and high IgG1, IgG2, and IgM titers, while the codon-optimized mRNA exhibited a stable secondary structure (ΔG = - 2,217.20 kcal/mol). These results suggest that antigen domain arrangement may influence predicted immunogenicity and structural stability, and exhibit a favorable in silico safety profile, supporting PPE68-IrtA-PE9 as a promising mRNA vaccine design for further experimental evaluation.
Journal article
2026-05-11T00:00:00+00:00
Epitope prediction, Tuberculosis, Vaccine design, Vaccine immunogenicity, mRNA vaccine