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PredβTM: A Novel β-Transmembrane Region Prediction Algorithm

Predicting the transmembrane regions is an important aspect of understanding the structures and architecture of different β-barrel membrane proteins. Despite significant efforts, currently available β-transmembrane region predictors are still limited in terms of prediction accuracy, especially in pr...

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Detalles Bibliográficos
Autores principales: Roy Choudhury, Amrita, Novič, Marjana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687927/
https://www.ncbi.nlm.nih.gov/pubmed/26694538
http://dx.doi.org/10.1371/journal.pone.0145564
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author Roy Choudhury, Amrita
Novič, Marjana
author_facet Roy Choudhury, Amrita
Novič, Marjana
author_sort Roy Choudhury, Amrita
collection PubMed
description Predicting the transmembrane regions is an important aspect of understanding the structures and architecture of different β-barrel membrane proteins. Despite significant efforts, currently available β-transmembrane region predictors are still limited in terms of prediction accuracy, especially in precision. Here, we describe PredβTM, a transmembrane region prediction algorithm for β-barrel proteins. Using amino acid pair frequency information in known β-transmembrane protein sequences, we have trained a support vector machine classifier to predict β-transmembrane segments. Position-specific amino acid preference data is incorporated in the final prediction. The predictor does not incorporate evolutionary profile information explicitly, but is based on sequence patterns generated implicitly by encoding the protein segments using amino acid adjacency matrix. With a benchmark set of 35 β-transmembrane proteins, PredβTM shows a sensitivity and precision of 83.71% and 72.98%, respectively. The segment overlap score is 82.19%. In comparison with other state-of-art methods, PredβTM provides a higher precision and segment overlap without compromising with sensitivity. Further, we applied PredβTM to analyze the β-barrel membrane proteins without defined transmembrane regions and the uncharacterized protein sequences in eight bacterial genomes and predict possible β-transmembrane proteins. PredβTM can be freely accessed on the web at http://transpred.ki.si/.
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spelling pubmed-46879272015-12-31 PredβTM: A Novel β-Transmembrane Region Prediction Algorithm Roy Choudhury, Amrita Novič, Marjana PLoS One Research Article Predicting the transmembrane regions is an important aspect of understanding the structures and architecture of different β-barrel membrane proteins. Despite significant efforts, currently available β-transmembrane region predictors are still limited in terms of prediction accuracy, especially in precision. Here, we describe PredβTM, a transmembrane region prediction algorithm for β-barrel proteins. Using amino acid pair frequency information in known β-transmembrane protein sequences, we have trained a support vector machine classifier to predict β-transmembrane segments. Position-specific amino acid preference data is incorporated in the final prediction. The predictor does not incorporate evolutionary profile information explicitly, but is based on sequence patterns generated implicitly by encoding the protein segments using amino acid adjacency matrix. With a benchmark set of 35 β-transmembrane proteins, PredβTM shows a sensitivity and precision of 83.71% and 72.98%, respectively. The segment overlap score is 82.19%. In comparison with other state-of-art methods, PredβTM provides a higher precision and segment overlap without compromising with sensitivity. Further, we applied PredβTM to analyze the β-barrel membrane proteins without defined transmembrane regions and the uncharacterized protein sequences in eight bacterial genomes and predict possible β-transmembrane proteins. PredβTM can be freely accessed on the web at http://transpred.ki.si/. Public Library of Science 2015-12-22 /pmc/articles/PMC4687927/ /pubmed/26694538 http://dx.doi.org/10.1371/journal.pone.0145564 Text en © 2015 Roy Choudhury, Novič 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
Roy Choudhury, Amrita
Novič, Marjana
PredβTM: A Novel β-Transmembrane Region Prediction Algorithm
title PredβTM: A Novel β-Transmembrane Region Prediction Algorithm
title_full PredβTM: A Novel β-Transmembrane Region Prediction Algorithm
title_fullStr PredβTM: A Novel β-Transmembrane Region Prediction Algorithm
title_full_unstemmed PredβTM: A Novel β-Transmembrane Region Prediction Algorithm
title_short PredβTM: A Novel β-Transmembrane Region Prediction Algorithm
title_sort predβtm: a novel β-transmembrane region prediction algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687927/
https://www.ncbi.nlm.nih.gov/pubmed/26694538
http://dx.doi.org/10.1371/journal.pone.0145564
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