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Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics
Candida dubliniensis is an opportunistic pathogen associated with oral and invasive fungal infections in immune-compromised individuals. Furthermore, the emergence of C. dubliniensis antifungal drug resistance could exacerbate its treatment. Hence, in this study a multi-epitope vaccine candidate has...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9964391/ https://www.ncbi.nlm.nih.gov/pubmed/36851241 http://dx.doi.org/10.3390/vaccines11020364 |
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author | Akhtar, Nahid Magdaleno, Jorge Samuel Leon Ranjan, Suryakant Wani, Atif Khurshid Grewal, Ravneet Kaur Oliva, Romina Shaikh, Abdul Rajjak Cavallo, Luigi Chawla, Mohit |
author_facet | Akhtar, Nahid Magdaleno, Jorge Samuel Leon Ranjan, Suryakant Wani, Atif Khurshid Grewal, Ravneet Kaur Oliva, Romina Shaikh, Abdul Rajjak Cavallo, Luigi Chawla, Mohit |
author_sort | Akhtar, Nahid |
collection | PubMed |
description | Candida dubliniensis is an opportunistic pathogen associated with oral and invasive fungal infections in immune-compromised individuals. Furthermore, the emergence of C. dubliniensis antifungal drug resistance could exacerbate its treatment. Hence, in this study a multi-epitope vaccine candidate has been designed using an immunoinformatics approach by targeting C. dubliniensis secreted aspartyl proteinases (SAP) proteins. In silico tools have been utilized to predict epitopes and determine their allergic potential, antigenic potential, toxicity, and potential to elicit interleukin-2 (IL2), interleukin-4 (IL4), and IFN-γ. Using the computational tools, eight epitopes have been predicted that were then linked with adjuvants for final vaccine candidate development. Computational immune simulation has depicted that the immunogen designed emerges as a strong immunogenic candidate for a vaccine. Further, molecular docking and molecular dynamics simulation analyses revealed stable interactions between the vaccine candidate and the human toll-like receptor 5 (TLR5). Finally, immune simulations corroborated the promising candidature of the designed vaccine, thus calling for further in vivo investigation. |
format | Online Article Text |
id | pubmed-9964391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99643912023-02-26 Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics Akhtar, Nahid Magdaleno, Jorge Samuel Leon Ranjan, Suryakant Wani, Atif Khurshid Grewal, Ravneet Kaur Oliva, Romina Shaikh, Abdul Rajjak Cavallo, Luigi Chawla, Mohit Vaccines (Basel) Article Candida dubliniensis is an opportunistic pathogen associated with oral and invasive fungal infections in immune-compromised individuals. Furthermore, the emergence of C. dubliniensis antifungal drug resistance could exacerbate its treatment. Hence, in this study a multi-epitope vaccine candidate has been designed using an immunoinformatics approach by targeting C. dubliniensis secreted aspartyl proteinases (SAP) proteins. In silico tools have been utilized to predict epitopes and determine their allergic potential, antigenic potential, toxicity, and potential to elicit interleukin-2 (IL2), interleukin-4 (IL4), and IFN-γ. Using the computational tools, eight epitopes have been predicted that were then linked with adjuvants for final vaccine candidate development. Computational immune simulation has depicted that the immunogen designed emerges as a strong immunogenic candidate for a vaccine. Further, molecular docking and molecular dynamics simulation analyses revealed stable interactions between the vaccine candidate and the human toll-like receptor 5 (TLR5). Finally, immune simulations corroborated the promising candidature of the designed vaccine, thus calling for further in vivo investigation. MDPI 2023-02-05 /pmc/articles/PMC9964391/ /pubmed/36851241 http://dx.doi.org/10.3390/vaccines11020364 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Akhtar, Nahid Magdaleno, Jorge Samuel Leon Ranjan, Suryakant Wani, Atif Khurshid Grewal, Ravneet Kaur Oliva, Romina Shaikh, Abdul Rajjak Cavallo, Luigi Chawla, Mohit Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics |
title | Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics |
title_full | Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics |
title_fullStr | Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics |
title_full_unstemmed | Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics |
title_short | Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics |
title_sort | secreted aspartyl proteinases targeted multi-epitope vaccine design for candida dubliniensis using immunoinformatics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9964391/ https://www.ncbi.nlm.nih.gov/pubmed/36851241 http://dx.doi.org/10.3390/vaccines11020364 |
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