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MemPype: a pipeline for the annotation of eukaryotic membrane proteins
MemPype is a Python-based pipeline including previously published methods for the prediction of signal peptides (SPEP), glycophosphatidylinositol (GPI) anchors (PredGPI), all-alpha membrane topology (ENSEMBLE), and a recent method (MemLoci) that specifically discriminates the localization of eukaryo...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3125734/ https://www.ncbi.nlm.nih.gov/pubmed/21543452 http://dx.doi.org/10.1093/nar/gkr282 |
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author | Pierleoni, Andrea Indio, Valentina Savojardo, Castrense Fariselli, Piero Martelli, Pier Luigi Casadio, Rita |
author_facet | Pierleoni, Andrea Indio, Valentina Savojardo, Castrense Fariselli, Piero Martelli, Pier Luigi Casadio, Rita |
author_sort | Pierleoni, Andrea |
collection | PubMed |
description | MemPype is a Python-based pipeline including previously published methods for the prediction of signal peptides (SPEP), glycophosphatidylinositol (GPI) anchors (PredGPI), all-alpha membrane topology (ENSEMBLE), and a recent method (MemLoci) that specifically discriminates the localization of eukaryotic membrane proteins in: ‘cell membrane’, ‘internal membranes’, ‘organelle membranes’. MemLoci scores with accuracy of 70% and generalized correlation coefficient (GCC) of 0.50 on a rigorous homology-unbiased validation set and overpasses other predictors for subcellular localization. The annotation process is based both on inheritance through homology and computational methods. Each submitted protein first retrieves, when available, up to 25 similar proteins (with sequence identity ≥50% and alignment coverage ≥50% on both sequences). This helps the identification of membrane-associated proteins and detailed localization tags. Each protein is also filtered for the presence of a GPI anchor [0.8% false positive rate (FPR)]. A positive score of GPI anchor prediction labels the sequence as exposed to ‘Cell surface’. Concomitantly the sequence is analysed for the presence of a signal peptide and classified with MemLoci into one of three discriminated classes. Finally the sequence is filtered for predicting its putative all-alpha protein membrane topology (FPR <1%). The web server is available at: http://mu2py.biocomp.unibo.it/mempype. |
format | Online Article Text |
id | pubmed-3125734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31257342011-07-05 MemPype: a pipeline for the annotation of eukaryotic membrane proteins Pierleoni, Andrea Indio, Valentina Savojardo, Castrense Fariselli, Piero Martelli, Pier Luigi Casadio, Rita Nucleic Acids Res Articles MemPype is a Python-based pipeline including previously published methods for the prediction of signal peptides (SPEP), glycophosphatidylinositol (GPI) anchors (PredGPI), all-alpha membrane topology (ENSEMBLE), and a recent method (MemLoci) that specifically discriminates the localization of eukaryotic membrane proteins in: ‘cell membrane’, ‘internal membranes’, ‘organelle membranes’. MemLoci scores with accuracy of 70% and generalized correlation coefficient (GCC) of 0.50 on a rigorous homology-unbiased validation set and overpasses other predictors for subcellular localization. The annotation process is based both on inheritance through homology and computational methods. Each submitted protein first retrieves, when available, up to 25 similar proteins (with sequence identity ≥50% and alignment coverage ≥50% on both sequences). This helps the identification of membrane-associated proteins and detailed localization tags. Each protein is also filtered for the presence of a GPI anchor [0.8% false positive rate (FPR)]. A positive score of GPI anchor prediction labels the sequence as exposed to ‘Cell surface’. Concomitantly the sequence is analysed for the presence of a signal peptide and classified with MemLoci into one of three discriminated classes. Finally the sequence is filtered for predicting its putative all-alpha protein membrane topology (FPR <1%). The web server is available at: http://mu2py.biocomp.unibo.it/mempype. Oxford University Press 2011-07-01 2011-05-04 /pmc/articles/PMC3125734/ /pubmed/21543452 http://dx.doi.org/10.1093/nar/gkr282 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Pierleoni, Andrea Indio, Valentina Savojardo, Castrense Fariselli, Piero Martelli, Pier Luigi Casadio, Rita MemPype: a pipeline for the annotation of eukaryotic membrane proteins |
title | MemPype: a pipeline for the annotation of eukaryotic membrane proteins |
title_full | MemPype: a pipeline for the annotation of eukaryotic membrane proteins |
title_fullStr | MemPype: a pipeline for the annotation of eukaryotic membrane proteins |
title_full_unstemmed | MemPype: a pipeline for the annotation of eukaryotic membrane proteins |
title_short | MemPype: a pipeline for the annotation of eukaryotic membrane proteins |
title_sort | mempype: a pipeline for the annotation of eukaryotic membrane proteins |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3125734/ https://www.ncbi.nlm.nih.gov/pubmed/21543452 http://dx.doi.org/10.1093/nar/gkr282 |
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