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bioRxiv · 10.64898/2026.07.09.737463

Computational design of a multi-epitope vaccine against M. tuberculosis

Buhari, A.·Okutu, P.·Oyeleke, U. A.·Sivakumar, A.·Hameed, S. A.
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Abstract

BackgroundTuberculosis remains a leading global infectious killer, with BCG offering inconsistent adult protection and rising drug-resistant strains demanding novel vaccine strategies. We report the first multi-epitope vaccine construct simultaneously targeting three previously unexplored Mycobacterium tuberculosis virulence proteins; EccB3, MycP, and polyketide synthase which collectively govern nutrient acquisition, ESX secretion integrity, and innate immune evasion. MethodsUsing a reverse vaccinology pipeline, B-cell, CTL, and HTL epitopes were predicted, filtered for allergenicity, toxicity, and IFN-{gamma} induction, then assembled into an 823-residue chimeric construct incorporating beta-defensin and PADRE adjuvants with AAY/GPGPG linkers, covering [~]90% global HLA diversity. The construct underwent AlphaFold structure prediction, 3DRefine refinement, disulfide engineering, PROCHECK/ProSA validation, ClusPro 2.0 docking against TLR1/TLR2, and C-IMMSIM immune simulation. ResultsThe construct (82.3 kDa, instability index 32.48) showed strong structural quality (94.7% favoured Ramachandran residues), stable TLR1/TLR2 binding (weighted energy: -1,371.0 kcal/mol), and robust in silico immune responses and durable memory cell formation following booster simulation. ConclusionThis computationally validated construct represents a promising multi-target TB vaccine candidate warranting experimental advancement.

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Buhari, A., Okutu, P., Oyeleke, U. A., Sivakumar, A., Hameed, S. A.. 2026-07-15. Computational design of a multi-epitope vaccine against M. tuberculosis. https://doi.org/10.64898/2026.07.09.737463

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