Immunoinformatics-guided in silico design of a multi-epitope peptide vaccine against Mycobacterium tuberculosis

Abstract

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) , remains a leading global health challenge, exacerbated by the limitations of the current Bacillus Calmette–Guérin (BCG) vaccine and the emergence of multidrug-resistant strains. Thus, there is a critical need for novel and safe vaccines capable of providing robust immune protection. This study aimed to design a multi-epitope peptide vaccine against Mtb using advanced immunoinformatics approaches. Conserved, antigenic, non-allergenic, and non-toxic Mtb proteins (Rv1196, Rv0978c, Rv2031c, Rv1886c and Rv3875) were selected and used to develop multi-epitope peptide vaccine construct. A comprehensive analysis was employed, including protein sequence retrieval, antigenicity and allergenicity prediction, epitope mapping, vaccine construct design with linkers and adjuvants, physiochemical profiling, structure prediction and validation, molecular docking and simulation, population coverage and immune simulation. After a comprehensive screening, five linear B-cell epitopes, four HTL epitopes, and nine CTL epitopes were selected to design a novel multi-epitope peptide vaccine for Mtb . The final multi-epitope peptide vaccine construct was 429 amino acids long, with a molecular weight of 43.947 kDa. The construct showed an instability index of 23.25, indicating overall stability, and an aliphatic index of 81.54, reflecting high thermostability. Its GRAVY score (0.021) suggested a predominantly hydrophilic nature, while the predicted scaled solubility score (0.451) indicated moderate solubility. According to PRISPRED prediction, the overall vaccine sequence was estimated to have 46.15% α-helix, 7.23% β-strand, and 46.62% coil. RaptorX-Property prediction also revealed 44% of amino-acid residues were expected to be exposed, 24% medium exposed, and 31% buried. The predicted 3D models of the vaccine construct were exhibited an estimated TM-score of 0.59 ± 0.14 and an expected RMSD of 9.2 ± 4.6 Å, indicating a reasonably accurate predicted fold. The vaccine construct docked with both TLR4 and TLR2, showing a stronger predicted binding affinity for TLR4 (–1175.2 kcal/mol) than for TLR2 (–1022.8 kcal/mol), and molecular dynamics simulations further confirmed stable and strong interactions with both receptors. The in-silico cloning, done to validate the vaccine’s efficacy. Finally, Immune simulation was applied to the vaccine to forecast its immunogenic profile. A computationally validated multi-epitope vaccine construct with strong immunogenicity were generated. However, validation through the in-vitro and in-vivo study of the developed vaccine is essential to assess its efficacy and immunogenicity profile, which will assure active protection against Mtb .