Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach
Leishmania tropica is a vector-borne parasitic protozoa that is the leading cause of leishmaniasis throughout the global tropics and subtropics. L. tropica is a multidrug-resistant parasite with a diverse set of serological, biochemical, and genomic features. There are currently no particular vaccin...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1259612/full |
| _version_ | 1827815346489262080 |
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| author | Sara Aiman Abbas Ahmad Azmat Ali Khan Amer M. Alanazi Abdus Samad Syed Luqman Ali Chunhua Li Zhiguang Ren Asifullah Khan Saadullah Khattak |
| author_facet | Sara Aiman Abbas Ahmad Azmat Ali Khan Amer M. Alanazi Abdus Samad Syed Luqman Ali Chunhua Li Zhiguang Ren Asifullah Khan Saadullah Khattak |
| author_sort | Sara Aiman |
| collection | DOAJ |
| description | Leishmania tropica is a vector-borne parasitic protozoa that is the leading cause of leishmaniasis throughout the global tropics and subtropics. L. tropica is a multidrug-resistant parasite with a diverse set of serological, biochemical, and genomic features. There are currently no particular vaccines available to combat leishmaniasis. The present study prioritized potential vaccine candidate proteins of L. tropica using subtractive proteomics and vaccinomics approaches. These vaccine candidate proteins were downstream analyzed to predict B- and T-cell epitopes based on high antigenicity, non-allergenic, and non-toxic characteristics. The top-ranked overlapping MHC-I, MHC-II, and linear B-cell epitopes were prioritized for model vaccine designing. The lead epitopes were linked together by suitable linker sequences to design multi-epitope constructs. Immunogenic adjuvant sequences were incorporated at the N-terminus of the model vaccine constructs to enhance their immunological potential. Among different combinations of constructs, four vaccine designs were selected based on their physicochemical and immunological features. The tertiary structure models of the designed vaccine constructs were predicted and verified. The molecular docking and molecular dynamic (MD) simulation analyses indicated that the vaccine design V1 demonstrated robust and stable molecular interactions with toll-like receptor 4 (TLR4). The top-ranked vaccine construct model-IV demonstrated significant expressive capability in the E. coli expression system during in-silico restriction cloning analysis. The results of the present study are intriguing; nevertheless, experimental bioassays are required to validate the efficacy of the predicted model chimeric vaccine. |
| first_indexed | 2024-03-11T23:58:53Z |
| format | Article |
| id | doaj.art-211516ce5dd74d83acd67d39a112b223 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-03-11T23:58:53Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-211516ce5dd74d83acd67d39a112b2232023-09-18T05:43:58ZengFrontiers Media S.A.Frontiers in Immunology1664-32242023-09-011410.3389/fimmu.2023.12596121259612Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approachSara Aiman0Abbas Ahmad1Azmat Ali Khan2Amer M. Alanazi3Abdus Samad4Syed Luqman Ali5Chunhua Li6Zhiguang Ren7Asifullah Khan8Saadullah Khattak9Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing, ChinaDepartment of Biotechnology, Abdul Wali Khan University Mardan, Mardan, PakistanPharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi ArabiaPharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi ArabiaDepartment of Biochemistry, Abdul Wali Khan University Mardan (AWKUM), Mardan, PakistanDepartment of Biochemistry, Abdul Wali Khan University Mardan (AWKUM), Mardan, PakistanFaculty of Environmental and Life Sciences, Beijing University of Technology, Beijing, ChinaThe First Affiliated Hospital, Henan University, Kaifeng, ChinaDepartment of Biochemistry, Abdul Wali Khan University Mardan (AWKUM), Mardan, PakistanHenan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng, Henan, ChinaLeishmania tropica is a vector-borne parasitic protozoa that is the leading cause of leishmaniasis throughout the global tropics and subtropics. L. tropica is a multidrug-resistant parasite with a diverse set of serological, biochemical, and genomic features. There are currently no particular vaccines available to combat leishmaniasis. The present study prioritized potential vaccine candidate proteins of L. tropica using subtractive proteomics and vaccinomics approaches. These vaccine candidate proteins were downstream analyzed to predict B- and T-cell epitopes based on high antigenicity, non-allergenic, and non-toxic characteristics. The top-ranked overlapping MHC-I, MHC-II, and linear B-cell epitopes were prioritized for model vaccine designing. The lead epitopes were linked together by suitable linker sequences to design multi-epitope constructs. Immunogenic adjuvant sequences were incorporated at the N-terminus of the model vaccine constructs to enhance their immunological potential. Among different combinations of constructs, four vaccine designs were selected based on their physicochemical and immunological features. The tertiary structure models of the designed vaccine constructs were predicted and verified. The molecular docking and molecular dynamic (MD) simulation analyses indicated that the vaccine design V1 demonstrated robust and stable molecular interactions with toll-like receptor 4 (TLR4). The top-ranked vaccine construct model-IV demonstrated significant expressive capability in the E. coli expression system during in-silico restriction cloning analysis. The results of the present study are intriguing; nevertheless, experimental bioassays are required to validate the efficacy of the predicted model chimeric vaccine.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1259612/fullleishmaniasisreverse vaccinologymulti-epitope vaccine designimmunoinformaticstropical diseasesvaccine design |
| spellingShingle | Sara Aiman Abbas Ahmad Azmat Ali Khan Amer M. Alanazi Abdus Samad Syed Luqman Ali Chunhua Li Zhiguang Ren Asifullah Khan Saadullah Khattak Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach Frontiers in Immunology leishmaniasis reverse vaccinology multi-epitope vaccine design immunoinformatics tropical diseases vaccine design |
| title | Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach |
| title_full | Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach |
| title_fullStr | Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach |
| title_full_unstemmed | Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach |
| title_short | Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach |
| title_sort | vaccinomics based next generation multi epitope chimeric vaccine models prediction against leishmania tropica a hierarchical subtractive proteomics and immunoinformatics approach |
| topic | leishmaniasis reverse vaccinology multi-epitope vaccine design immunoinformatics tropical diseases vaccine design |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1259612/full |
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