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.

Copyright: © 2026 Liaqat et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.