CP91110P: A Computationally Designed Multi-Epitope Vaccine Candidate for Tuberculosis via TLR-2/4 Synergistic Immunomodulation

Yajing An, Syed Luqman Ali, Yanhua Liu, Aigul Abduldayeva, Ruizi Ni, Yufeng Li, Mingming Zhang, Yuan Tian, Lina Jiang, Wenping Gong

2025

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.3390/biology14091196
Data confidence 70 medium
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Abstract

Background: Tuberculosis (TB) remains a global health priority, with current interventions like the Bacille Calmette–Guérin (BCG) vaccine lacking efficacy against latent infection and drug-resistant strains. Novel vaccines targeting both latent and active TB are urgently needed. Objective: This study aims to design a multi-epitope vaccine (MEV) and evaluate its immunogenicity, structural stability, and interactions with toll-like receptor 2/4 (TLR-2/4) via computational biology approaches. Methods: We designed MEV using bioinformatics tools, prioritizing immunodominant epitopes from Mycobacterium tuberculosis antigens. Structural stability was optimized through disulfide engineering, and molecular docking/dynamics simulations were used to analyze interactions and conformational dynamics with TLR-2/4. Antigenicity, immunogenicity, population coverage, and immune responses were computationally assessed. Results: The MEV candidate, CP91110P, exhibited 86.18% predicted global human leukocyte antigen (HLA)-I/II coverage, high antigenicity (VaxiJen: 0.8789), and immunogenicity (IEDB: 4.40091), with favorable stability (instability index: 33.48) and solubility (0.485). Tertiary structure analysis indicated that 98.34% residues were located in favored regions. Molecular docking suggested strong TLR-2 (−1535.9 kcal/mol) and TLR-4 (−1672.5 kcal/mol) binding. Molecular dynamics simulations indicated stable TLR-2 interactions (RMSD: 6–8 Å; Rg: 38.50–39.50 Å) and flexible TLR-4 binding (RMSD: 2–6 Å; Rg: 33–36 Å). Principal component analysis, free energy landscapes, and dynamic cross-correlation matrix analyses highlighted TLR-2’s structural coherence versus TLR-4’s adaptive flexibility. Immune simulations predicted potential robust natural killer cell activation, T helper 1 polarization (interferon-gamma/interleukin-2 dominance), and elevated IgM/IgG levels. Conclusions: CP91110P is predicted to stably bind to TLR-2 and flexibly interact with TLR-4, with prediction of its high antigenicity and broad coverage across immune populations. However, this conclusion requires confirmation through experimental validation. Therefore, it may provide a promising candidate for experimental validation in the development of tuberculosis vaccines.