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

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

Background Tuberculosis 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. Methods Using a reverse vaccinology pipeline, B-cell, CTL, and HTL epitopes were predicted, filtered for allergenicity, toxicity, and IFN-γ 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. Results The 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. Conclusion This computationally validated construct represents a promising multi-target TB vaccine candidate warranting experimental advancement.

In silico framework for designing and validating a multi-stage subunit vaccine against Tuberculosis using reverse vaccinology approach

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a critical public health concern due to the limited efficacy of the Bacillus Calmette-Guerin (BCG) vaccine, the only WHO-approved vaccine so far. Based on the reverse vaccinology approach, this study involves in silico prediction of a fusion constructed from four highly immunogenic antigens from the latent, early, and active stages of the disease. The fusion named TetraFuVac11 consists of the complete sequences of the antigens CFP-7 and EspC and the truncated sequences of the antigens HspX and Hrp1. Major Histocompatibility Complex II (MHC II) binding Th-cell-specific epitopes were predicted through tools provided in the Immune Epitope Database (IEDB). The designed fusion molecule was found to be antigenic, non-allergenic and non-toxic. The instability index II and the GRAND Average of Hydropathy values were predicted to be 29.51 and −0.182, respectively. The refinement of the predicted 3D structure resulted in an improved stereochemical profile. The Z-score was predicted to be −6.8, and the ERRAT score was improved from 94.928 for the unrefined model to 97.1591 for the refined model. The data obtained from molecular dynamics (MD) simulations and Normal Mode Analysis (NMA) of the docked complex between the refined fusion protein and Toll-like Receptor 4 (TLR4) demonstrated a s interaction. The fusion construct was successfully predicted to be cloned into the pET-28a(+) vector to make a recombinant plasmid. The predicted solubility of the fusion protein exceeded the threshold values, indicating soluble expression in Escherichia coli. Finally, based on the encouraging in silico data, the proposed construct could serve as a potential vaccine candidate for detailed experimental validation towards developing an Mtb-specific vaccine.

Immunoinformatics-Based Multi-Epitope Vaccine Design Against Influenza A (H1N1) Hemagglutinin

The designed HA-based multi-epitope vaccine demonstrated promising immunogenicity, safety, structural stability, and broad population coverage in silico, and its potential as a vaccine candidate against Influenza A (H1N1) is supported.

Design of a multi-epitope vaccine against Mycobacterium tuberculosis using reverse vaccinology and immunoreactive peptides

PE/PPE proteins and TCR-recognized immunoreactive peptides are suggested as promising vaccine components against tuberculosis and the designed MEV with the C-terminal fragment of CPE may represent a potential candidate for future development as a mucosal vaccine against M. tuberculosis.

Immunoinformatics-guided design of a conserved multi-epitope vaccine candidate against pathogenic human coronaviruses.

Leveraging immunoinformatic techniques for the development of a multi-epitope subunit vaccine targeting virulence-associated proteins of Mycobacterium tuberculosis

Among infectious diseases, tuberculosis is the biggest cause of death worldwide. Thus, controlling TB, a global epidemic, is a major public health concern on a worldwide scale. According to epidemiological modelling, a new vaccination that can prevent TB, especially in adults and adolescents, is necessary to control the disease’s spread, even while medication therapies for the disease are still improving. The development of novel vaccines with broader applicability and improved, long-lasting effectiveness becomes increasingly crucial as strains resistant to various drugs emerge. This work designed a multi-epitope subunit vaccine (MESV) candidateusing immunoinformatic approaches that targets five virulence-associated proteins, Rv0227c, Rv0584, Lipoprotein LprA, Phospholipase C, and Antigen 85 C. Antigenicity, non-allergenicity, and non-toxicity were the criteria used to identify and filter potential CTL, HTL, and B-cell epitopes. High-affinity epitopes connected with suitable spacers and an adjuvant for improved immunogenicity were included in the carried-out vaccine formulation. Validation and structural modelling verified the MESV’s quality and stability. TLR2 and TLR4 receptors have strong interactions, which were further demonstrated through molecular docking, and molecular dynamics simulations showed low fluctuations and good structural stability. Further, the MMPBSA analysis was introduced to determine the binding affinity of the vaccine construct, and a more pronounced binding affinity was established by the designed vaccine with TLR4. Increased cytokine release, memory cell development, and the developed MESV candidateare viable options warranting further experimental validation, as it may elicit potent humoral and cellular immune responses against M. tuberculosis.