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An Immuno-informatics driven Epitope study from the molecular interaction of JEV non-structural (NS) proteins with Ribophorin (RPN)
Japanese encephalitis (JE) is an acute viral infection of the central nervous system where the JE virus infects the lumen of the endoplasmic reticulum (ER) and rapidly accumulates substantial amount of seven different nonstructural proteins (NS). These NS proteins tend to bind on a glycoprotein rece...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4166768/ https://www.ncbi.nlm.nih.gov/pubmed/25258484 http://dx.doi.org/10.6026/97320630010496 |
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author | Sayeed, Usman Wadhwa, Gulshan Khan, M Kalim A Jamal, Qazi Mohd Sajid Akhtar, Salman Khan, M Salman |
author_facet | Sayeed, Usman Wadhwa, Gulshan Khan, M Kalim A Jamal, Qazi Mohd Sajid Akhtar, Salman Khan, M Salman |
author_sort | Sayeed, Usman |
collection | PubMed |
description | Japanese encephalitis (JE) is an acute viral infection of the central nervous system where the JE virus infects the lumen of the endoplasmic reticulum (ER) and rapidly accumulates substantial amount of seven different nonstructural proteins (NS). These NS proteins tend to bind on a glycoprotein receptor, ribophorin (RPN) resulting in the malfunctioning of ER in host cells, subsequently triggering an unfolded protein response. Therefore, it is of interest to predict the best possible antigenic determinants in the NS protein capable of eliciting immune response as a strategy to combat JE. Hence, it is our interest to explore the most potent NS protein among all showing the best possible molecular interaction with the RPN receptor present on ER. However, the structures of these NS protein and RPN are currently unknown. Thus, we modeled their structures using the established homology modeling techniques in the MODELLER 9v10 software. The molecular docking of NS proteins with RPN was subsequently completed using the Discovery Studio 2.5 software suite. The docked conformations of RPN with NS were further analyzed and its graphical interpretations were presented for identifying the most potential NS protein for efficient epitope activity. Further, the B cell epitopes were mapped using BCPred and the predicted epitope regions are documented. The data presented in this report provides useful insights towards the design and development of potential epitopes to generate a vaccine candidate against JEV. |
format | Online Article Text |
id | pubmed-4166768 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Biomedical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-41667682014-09-25 An Immuno-informatics driven Epitope study from the molecular interaction of JEV non-structural (NS) proteins with Ribophorin (RPN) Sayeed, Usman Wadhwa, Gulshan Khan, M Kalim A Jamal, Qazi Mohd Sajid Akhtar, Salman Khan, M Salman Bioinformation Hypothesis Japanese encephalitis (JE) is an acute viral infection of the central nervous system where the JE virus infects the lumen of the endoplasmic reticulum (ER) and rapidly accumulates substantial amount of seven different nonstructural proteins (NS). These NS proteins tend to bind on a glycoprotein receptor, ribophorin (RPN) resulting in the malfunctioning of ER in host cells, subsequently triggering an unfolded protein response. Therefore, it is of interest to predict the best possible antigenic determinants in the NS protein capable of eliciting immune response as a strategy to combat JE. Hence, it is our interest to explore the most potent NS protein among all showing the best possible molecular interaction with the RPN receptor present on ER. However, the structures of these NS protein and RPN are currently unknown. Thus, we modeled their structures using the established homology modeling techniques in the MODELLER 9v10 software. The molecular docking of NS proteins with RPN was subsequently completed using the Discovery Studio 2.5 software suite. The docked conformations of RPN with NS were further analyzed and its graphical interpretations were presented for identifying the most potential NS protein for efficient epitope activity. Further, the B cell epitopes were mapped using BCPred and the predicted epitope regions are documented. The data presented in this report provides useful insights towards the design and development of potential epitopes to generate a vaccine candidate against JEV. Biomedical Informatics 2014-08-30 /pmc/articles/PMC4166768/ /pubmed/25258484 http://dx.doi.org/10.6026/97320630010496 Text en © 2014 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited. |
spellingShingle | Hypothesis Sayeed, Usman Wadhwa, Gulshan Khan, M Kalim A Jamal, Qazi Mohd Sajid Akhtar, Salman Khan, M Salman An Immuno-informatics driven Epitope study from the molecular interaction of JEV non-structural (NS) proteins with Ribophorin (RPN) |
title | An Immuno-informatics driven Epitope study from the molecular interaction of JEV non-structural (NS) proteins with Ribophorin (RPN) |
title_full | An Immuno-informatics driven Epitope study from the molecular interaction of JEV non-structural (NS) proteins with Ribophorin (RPN) |
title_fullStr | An Immuno-informatics driven Epitope study from the molecular interaction of JEV non-structural (NS) proteins with Ribophorin (RPN) |
title_full_unstemmed | An Immuno-informatics driven Epitope study from the molecular interaction of JEV non-structural (NS) proteins with Ribophorin (RPN) |
title_short | An Immuno-informatics driven Epitope study from the molecular interaction of JEV non-structural (NS) proteins with Ribophorin (RPN) |
title_sort | immuno-informatics driven epitope study from the molecular interaction of jev non-structural (ns) proteins with ribophorin (rpn) |
topic | Hypothesis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4166768/ https://www.ncbi.nlm.nih.gov/pubmed/25258484 http://dx.doi.org/10.6026/97320630010496 |
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