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Rapid membrane protein topology prediction

Summary: State-of-the-art methods for topology of α-helical membrane proteins are based on the use of time-consuming multiple sequence alignments obtained from PSI-BLAST or other sources. Here, we examine if it is possible to use the consensus of topology prediction methods that are based on single...

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Detalles Bibliográficos
Autores principales: Hennerdal, Aron, Elofsson, Arne
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3077071/
https://www.ncbi.nlm.nih.gov/pubmed/21493661
http://dx.doi.org/10.1093/bioinformatics/btr119
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author Hennerdal, Aron
Elofsson, Arne
author_facet Hennerdal, Aron
Elofsson, Arne
author_sort Hennerdal, Aron
collection PubMed
description Summary: State-of-the-art methods for topology of α-helical membrane proteins are based on the use of time-consuming multiple sequence alignments obtained from PSI-BLAST or other sources. Here, we examine if it is possible to use the consensus of topology prediction methods that are based on single sequences to obtain a similar accuracy as the more accurate multiple sequence-based methods. Here, we show that TOPCONS-single performs better than any of the other topology prediction methods tested here, but ∼6% worse than the best method that is utilizing multiple sequence alignments. Availability and Implementation: TOPCONS-single is available as a web server from http://single.topcons.net/ and is also included for local installation from the web site. In addition, consensus-based topology predictions for the entire international protein index (IPI) is available from the web server and will be updated at regular intervals. Contact: arne@bioinfo.se Supplementary information: Supplementary data are avaliable at Bioinformatics online.
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spelling pubmed-30770712011-04-14 Rapid membrane protein topology prediction Hennerdal, Aron Elofsson, Arne Bioinformatics Applications Note Summary: State-of-the-art methods for topology of α-helical membrane proteins are based on the use of time-consuming multiple sequence alignments obtained from PSI-BLAST or other sources. Here, we examine if it is possible to use the consensus of topology prediction methods that are based on single sequences to obtain a similar accuracy as the more accurate multiple sequence-based methods. Here, we show that TOPCONS-single performs better than any of the other topology prediction methods tested here, but ∼6% worse than the best method that is utilizing multiple sequence alignments. Availability and Implementation: TOPCONS-single is available as a web server from http://single.topcons.net/ and is also included for local installation from the web site. In addition, consensus-based topology predictions for the entire international protein index (IPI) is available from the web server and will be updated at regular intervals. Contact: arne@bioinfo.se Supplementary information: Supplementary data are avaliable at Bioinformatics online. Oxford University Press 2011-05-01 2011-04-13 /pmc/articles/PMC3077071/ /pubmed/21493661 http://dx.doi.org/10.1093/bioinformatics/btr119 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Hennerdal, Aron
Elofsson, Arne
Rapid membrane protein topology prediction
title Rapid membrane protein topology prediction
title_full Rapid membrane protein topology prediction
title_fullStr Rapid membrane protein topology prediction
title_full_unstemmed Rapid membrane protein topology prediction
title_short Rapid membrane protein topology prediction
title_sort rapid membrane protein topology prediction
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3077071/
https://www.ncbi.nlm.nih.gov/pubmed/21493661
http://dx.doi.org/10.1093/bioinformatics/btr119
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