In Silico Targeting and Immunological Profiling of PpiA in <i>Mycobacterium tuberculosis</i>: A Computational Approach
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...
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MDPI AG
2025-04-01
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| author | Mohammad J. Nasiri Lily Rogowski Vishwanath Venketaraman |
| author_facet | Mohammad J. Nasiri Lily Rogowski Vishwanath Venketaraman |
| author_sort | Mohammad J. Nasiri |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-212da3d9d36742dabc3f03b267dacbef |
| institution | OA Journals |
| issn | 2076-0817 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Pathogens |
| spelling | doaj-art-212da3d9d36742dabc3f03b267dacbef2025-08-20T02:28:38ZengMDPI AGPathogens2076-08172025-04-0114437010.3390/pathogens14040370In Silico Targeting and Immunological Profiling of PpiA in <i>Mycobacterium tuberculosis</i>: A Computational ApproachMohammad J. Nasiri0Lily Rogowski1Vishwanath Venketaraman2Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 19839-69411, IranCollege of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766-1854, USACollege of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766-1854, USATuberculosis (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.https://www.mdpi.com/2076-0817/14/4/370tuberculosis vaccinepeptidyl-prolyl isomerase A (PpiA)immunoinformaticepitope predictionB-cell epitopesT-cell epitopes |
| spellingShingle | Mohammad J. Nasiri Lily Rogowski Vishwanath Venketaraman In Silico Targeting and Immunological Profiling of PpiA in <i>Mycobacterium tuberculosis</i>: A Computational Approach Pathogens tuberculosis vaccine peptidyl-prolyl isomerase A (PpiA) immunoinformatic epitope prediction B-cell epitopes T-cell epitopes |
| title | In Silico Targeting and Immunological Profiling of PpiA in <i>Mycobacterium tuberculosis</i>: A Computational Approach |
| title_full | In Silico Targeting and Immunological Profiling of PpiA in <i>Mycobacterium tuberculosis</i>: A Computational Approach |
| title_fullStr | In Silico Targeting and Immunological Profiling of PpiA in <i>Mycobacterium tuberculosis</i>: A Computational Approach |
| title_full_unstemmed | In Silico Targeting and Immunological Profiling of PpiA in <i>Mycobacterium tuberculosis</i>: A Computational Approach |
| title_short | In Silico Targeting and Immunological Profiling of PpiA in <i>Mycobacterium tuberculosis</i>: A Computational Approach |
| title_sort | in silico targeting and immunological profiling of ppia in i mycobacterium tuberculosis i a computational approach |
| topic | tuberculosis vaccine peptidyl-prolyl isomerase A (PpiA) immunoinformatic epitope prediction B-cell epitopes T-cell epitopes |
| url | https://www.mdpi.com/2076-0817/14/4/370 |
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