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Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico

The internal ribosomal entry site (IRES) functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES el...

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Autores principales: Hong, Jun-Jie, Wu, Tzong-Yuan, Chang, Tsair-Yuan, Chen, Chung-Yung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3818432/
https://www.ncbi.nlm.nih.gov/pubmed/24223923
http://dx.doi.org/10.1371/journal.pone.0079288
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author Hong, Jun-Jie
Wu, Tzong-Yuan
Chang, Tsair-Yuan
Chen, Chung-Yung
author_facet Hong, Jun-Jie
Wu, Tzong-Yuan
Chang, Tsair-Yuan
Chen, Chung-Yung
author_sort Hong, Jun-Jie
collection PubMed
description The internal ribosomal entry site (IRES) functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS) to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/.
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spelling pubmed-38184322013-11-09 Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico Hong, Jun-Jie Wu, Tzong-Yuan Chang, Tsair-Yuan Chen, Chung-Yung PLoS One Research Article The internal ribosomal entry site (IRES) functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS) to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/. Public Library of Science 2013-11-05 /pmc/articles/PMC3818432/ /pubmed/24223923 http://dx.doi.org/10.1371/journal.pone.0079288 Text en © 2013 Hong et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Hong, Jun-Jie
Wu, Tzong-Yuan
Chang, Tsair-Yuan
Chen, Chung-Yung
Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico
title Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico
title_full Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico
title_fullStr Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico
title_full_unstemmed Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico
title_short Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico
title_sort viral ires prediction system - a web server for prediction of the ires secondary structure in silico
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3818432/
https://www.ncbi.nlm.nih.gov/pubmed/24223923
http://dx.doi.org/10.1371/journal.pone.0079288
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