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Concomitant prediction of function and fold at the domain level with GO-based profiles
Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocate...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3584904/ https://www.ncbi.nlm.nih.gov/pubmed/23514233 http://dx.doi.org/10.1186/1471-2105-14-S3-S12 |
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author | Lopez, Daniel Pazos, Florencio |
author_facet | Lopez, Daniel Pazos, Florencio |
author_sort | Lopez, Daniel |
collection | PubMed |
description | Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required. We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function. |
format | Online Article Text |
id | pubmed-3584904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35849042013-03-11 Concomitant prediction of function and fold at the domain level with GO-based profiles Lopez, Daniel Pazos, Florencio BMC Bioinformatics Proceedings Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required. We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function. BioMed Central 2013-02-28 /pmc/articles/PMC3584904/ /pubmed/23514233 http://dx.doi.org/10.1186/1471-2105-14-S3-S12 Text en Copyright ©2013 Lopez and Pazos; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Lopez, Daniel Pazos, Florencio Concomitant prediction of function and fold at the domain level with GO-based profiles |
title | Concomitant prediction of function and fold at the domain level with GO-based profiles |
title_full | Concomitant prediction of function and fold at the domain level with GO-based profiles |
title_fullStr | Concomitant prediction of function and fold at the domain level with GO-based profiles |
title_full_unstemmed | Concomitant prediction of function and fold at the domain level with GO-based profiles |
title_short | Concomitant prediction of function and fold at the domain level with GO-based profiles |
title_sort | concomitant prediction of function and fold at the domain level with go-based profiles |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3584904/ https://www.ncbi.nlm.nih.gov/pubmed/23514233 http://dx.doi.org/10.1186/1471-2105-14-S3-S12 |
work_keys_str_mv | AT lopezdaniel concomitantpredictionoffunctionandfoldatthedomainlevelwithgobasedprofiles AT pazosflorencio concomitantpredictionoffunctionandfoldatthedomainlevelwithgobasedprofiles |