Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico
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| Authors: | Jun-Jie Hong Tzong-Yuan Wu Tsair-Yuan Chang Chung-Yung Chen |
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| Institution: | 1. Department of Bioscience Technology, Chung Yuan Christian University, Chung-Li, Taiwan.; 2. Center for Nanotechnology and Institute of Biomedical Technology, Chung Yuan Christian University, Chung-Li, Taiwan.; 3. R&D Center of Membrane Technology, Chung Yuan Christian University, Chung-Li, Taiwan.; 4. Information Management Department, Ming Chuan University, Guishan Township, Taoyuan, County, Taiwan.; University of Rome, Italy, |
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| Abstract: | 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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