Development of a Multi-epitope Vaccine against Mycobacterium tuberculosis DNA Protein B: An Immunoinformatics-Driven Strategy

Abstract

Vaccination is a primary strategy in the prevention of tuberculosis (TB), a serious infectious disease caused by Mycobacterium tuberculosis. This study aims to design a novel multiepitope vaccine using the DNA B protein from M. tuberculosis through immunoinformatics and molecular dynamics approaches. The design process begins with the identification of potential epitopes from the DNA B protein using various bioinformatics tools to predict both B and T cell epitopes based on their immunogenic properties. After epitope identification, the selected epitopes are combined into a multiepitope vaccine construct to enhance a broad and specific immune response. The three-dimensional structural model of the vaccine construct is predicted and validated using molecular modeling techniques. Molecular dynamics simulations are performed to evaluate the stability and interactions between the multiepitope vaccine and the immune system, providing insights into the expected immune response. Simulation analysis indicates that the vaccine construct is stable and capable of eliciting a strong immune response. In silico testing was conducted to predict the vaccine's affinity for Major Histocompatibility Complex (MHC) receptors and its ability to induce T and B cell immune responses. The results of this analysis demonstrate that the designed multiepitope vaccine has high potential to trigger an effective immune response against Mycobacterium tuberculosis. This study provides a solid foundation for further development and evaluation of the vaccine in in vivo studies to determine its clinical safety and efficacy