Optimizing a Subunit Vaccine of Mycobacterium tuberculosis Using In-Silico and In-Vitro Approaches
Zaiqin Ling, Muhammad Ahsan Naeem
Iranian Journal of Public Health · 2025-10
Abstract
Background: The present study addresses the development of a novel subunit vaccine (SV) to combat tuberculosis (TB). Methods: The research used immunoinformatics to develop a subunit vaccine with 7 MHC-I, 3 MHC-II, and 7 B-cell epitopes joined by AAV, GPGPG, and KK linkers. It involved Mtb protein Rv0577 and PADRE sequence as an adjuvant. TLR2 binding affinity (Kd, nM) was determined through PRODIGY. In-silico evaluations determined allergenicity, antigenicity, and physicochemical properties. The vaccine was presented in an AAVDj/8 system, intracellular expression was verified, and the copy number was identified using qPCR and qRT-PCR. Results: The web tools confirmed the stability, non-allergenicity, and high immunogenicity of the vaccine (0.5673 < 0.4). PRODIGY tool depicted good SV-TLR2 binding (ΔG = -8.8 kcal/mol, Kd = 330 nM) with 59 intermolecular contacts, indicating possible TLR2 activation. Indirect immunofluorescence showed the expression of intracellular proteins. Viral titers, determined by 10-fold serial dilution up to 10³, showed a detectable titer, and copy numbers (10⁹/mL–10¹¹/mL) proved productive viral replication and significant vaccine effectiveness. Conclusion: This comprehensive methodology, from epitope selection to in-vitro testing, establishes a robust foundation for further exploring and advancing this SV.
MeSH terms
- Mycobacterium tuberculosis
- Virology
- Protein subunit
- Epitope
- Biology
- Selection (genetic algorithm)
- Computational biology
- Tuberculosis vaccines
- Tuberculosis
- Microbiology
- Foundation (evidence)