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SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions
Large portions of higher eukaryotic proteomes are intrinsically disordered, and abundant evidence suggests that these unstructured regions of proteins are rich in regulatory interaction interfaces. A major class of disordered interaction interfaces are the compact and degenerate modules known as sho...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3510515/ https://www.ncbi.nlm.nih.gov/pubmed/22977176 http://dx.doi.org/10.1093/nar/gks854 |
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author | Davey, Norman E. Cowan, Joanne L. Shields, Denis C. Gibson, Toby J. Coldwell, Mark J. Edwards, Richard J. |
author_facet | Davey, Norman E. Cowan, Joanne L. Shields, Denis C. Gibson, Toby J. Coldwell, Mark J. Edwards, Richard J. |
author_sort | Davey, Norman E. |
collection | PubMed |
description | Large portions of higher eukaryotic proteomes are intrinsically disordered, and abundant evidence suggests that these unstructured regions of proteins are rich in regulatory interaction interfaces. A major class of disordered interaction interfaces are the compact and degenerate modules known as short linear motifs (SLiMs). As a result of the difficulties associated with the experimental identification and validation of SLiMs, our understanding of these modules is limited, advocating the use of computational methods to focus experimental discovery. This article evaluates the use of evolutionary conservation as a discriminatory technique for motif discovery. A statistical framework is introduced to assess the significance of relatively conserved residues, quantifying the likelihood a residue will have a particular level of conservation given the conservation of the surrounding residues. The framework is expanded to assess the significance of groupings of conserved residues, a metric that forms the basis of SLiMPrints (short linear motif fingerprints), a de novo motif discovery tool. SLiMPrints identifies relatively overconstrained proximal groupings of residues within intrinsically disordered regions, indicative of putatively functional motifs. Finally, the human proteome is analysed to create a set of highly conserved putative motif instances, including a novel site on translation initiation factor eIF2A that may regulate translation through binding of eIF4E. |
format | Online Article Text |
id | pubmed-3510515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-35105152012-11-30 SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions Davey, Norman E. Cowan, Joanne L. Shields, Denis C. Gibson, Toby J. Coldwell, Mark J. Edwards, Richard J. Nucleic Acids Res Computational Biology Large portions of higher eukaryotic proteomes are intrinsically disordered, and abundant evidence suggests that these unstructured regions of proteins are rich in regulatory interaction interfaces. A major class of disordered interaction interfaces are the compact and degenerate modules known as short linear motifs (SLiMs). As a result of the difficulties associated with the experimental identification and validation of SLiMs, our understanding of these modules is limited, advocating the use of computational methods to focus experimental discovery. This article evaluates the use of evolutionary conservation as a discriminatory technique for motif discovery. A statistical framework is introduced to assess the significance of relatively conserved residues, quantifying the likelihood a residue will have a particular level of conservation given the conservation of the surrounding residues. The framework is expanded to assess the significance of groupings of conserved residues, a metric that forms the basis of SLiMPrints (short linear motif fingerprints), a de novo motif discovery tool. SLiMPrints identifies relatively overconstrained proximal groupings of residues within intrinsically disordered regions, indicative of putatively functional motifs. Finally, the human proteome is analysed to create a set of highly conserved putative motif instances, including a novel site on translation initiation factor eIF2A that may regulate translation through binding of eIF4E. Oxford University Press 2012-11 2012-09-12 /pmc/articles/PMC3510515/ /pubmed/22977176 http://dx.doi.org/10.1093/nar/gks854 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Davey, Norman E. Cowan, Joanne L. Shields, Denis C. Gibson, Toby J. Coldwell, Mark J. Edwards, Richard J. SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions |
title | SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions |
title_full | SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions |
title_fullStr | SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions |
title_full_unstemmed | SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions |
title_short | SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions |
title_sort | slimprints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3510515/ https://www.ncbi.nlm.nih.gov/pubmed/22977176 http://dx.doi.org/10.1093/nar/gks854 |
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