In Silico Targeting and Immunological Profiling of PpiA in Mycobacterium tuberculosis: A Computational Approach

利用计算机模拟方法对结核分枝杆菌中的 PpiA 进行靶向和免疫学分析:一种计算方法

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Abstract

Tuberculosis (TB) remains a leading cause of mortality, with drug resistance highlighting the need for new vaccine targets. Peptidyl-prolyl isomerase A (PpiA), a conserved Mycobacterium tuberculosis (Mtb) protein, plays a role in bacterial stress adaptation and immune evasion, making it a potential target for immunotherapy. This study uses computational methods to assess PpiA's antigenicity, structural integrity, and immunogenic potential. The PpiA sequence was retrieved from NCBI and analyzed for antigenicity and allergenicity using VaxiJen, AllerTOP, and AllergenFP. Physicochemical properties were evaluated using ProtParam, and structural models were generated through PSIPRED and SWISS-MODEL. Structural validation was performed with MolProbity, QMEANDisCo, and ProSA-Web. B-cell epitopes were predicted using BepiPred 2.0 and IEDB, while T-cell epitopes were mapped via IEDB's MHC-I and MHC-II tools. Epitope conservation across Mtb strains was confirmed using ConSurf. Results indicate PpiA is highly antigenic, non-allergenic, and stable, with several immunogenic epitopes identified for both B- and T-cells. This study supports PpiA as a promising immunogenic target for TB vaccine development.

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