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MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction
Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels, transporters, receptors. Because it is difficult to determinate the membrane protein’s structure by wet-lab experiments, accurate and fast amino ac...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6199043/ https://www.ncbi.nlm.nih.gov/pubmed/30393651 http://dx.doi.org/10.1007/s40820-017-0156-2 |
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author | Yin, Xi Yang, Jing Xiao, Feng Yang, Yang Shen, Hong-Bin |
author_facet | Yin, Xi Yang, Jing Xiao, Feng Yang, Yang Shen, Hong-Bin |
author_sort | Yin, Xi |
collection | PubMed |
description | Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels, transporters, receptors. Because it is difficult to determinate the membrane protein’s structure by wet-lab experiments, accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called MemBrain, whose input is the amino acid sequence. MemBrain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of α-helical membrane proteins. MemBrain achieves a prediction accuracy of 97.9% of A (TMH), 87.1% of A (P), 3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. MemBrain-Contact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction, respectively. And MemBrain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of 13.593. These prediction results provide valuable hints for revealing the structure and function of membrane proteins. MemBrain web server is free for academic use and available at www.csbio.sjtu.edu.cn/bioinf/MemBrain/. [Image: see text] |
format | Online Article Text |
id | pubmed-6199043 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-61990432018-11-02 MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction Yin, Xi Yang, Jing Xiao, Feng Yang, Yang Shen, Hong-Bin Nanomicro Lett Article Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels, transporters, receptors. Because it is difficult to determinate the membrane protein’s structure by wet-lab experiments, accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called MemBrain, whose input is the amino acid sequence. MemBrain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of α-helical membrane proteins. MemBrain achieves a prediction accuracy of 97.9% of A (TMH), 87.1% of A (P), 3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. MemBrain-Contact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction, respectively. And MemBrain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of 13.593. These prediction results provide valuable hints for revealing the structure and function of membrane proteins. MemBrain web server is free for academic use and available at www.csbio.sjtu.edu.cn/bioinf/MemBrain/. [Image: see text] Springer Berlin Heidelberg 2017-09-27 /pmc/articles/PMC6199043/ /pubmed/30393651 http://dx.doi.org/10.1007/s40820-017-0156-2 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Yin, Xi Yang, Jing Xiao, Feng Yang, Yang Shen, Hong-Bin MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction |
title | MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction |
title_full | MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction |
title_fullStr | MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction |
title_full_unstemmed | MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction |
title_short | MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction |
title_sort | membrain: an easy-to-use online webserver for transmembrane protein structure prediction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6199043/ https://www.ncbi.nlm.nih.gov/pubmed/30393651 http://dx.doi.org/10.1007/s40820-017-0156-2 |
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