Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.

With the exponential increase in the number of sequenced organisms, automated annotation of proteins is becoming increasingly important. Intrinsically disordered regions are known to play a significant role in protein function. Despite their abundance, especially in eukaryotes, they are rarely used...

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Autores principales:	Alok Sharma, Abdollah Dehzangi, James Lyons, Seiya Imoto, Satoru Miyano, Kenta Nakai, Ashwini Patil
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/524d9657344049c3aeef6794bb47771b
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spelling	oai:doaj.org-article:524d9657344049c3aeef6794bb47771b2021-11-18T08:31:14ZEvaluation of sequence features from intrinsically disordered regions for the estimation of protein function.1932-620310.1371/journal.pone.0089890https://doaj.org/article/524d9657344049c3aeef6794bb47771b2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24587103/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203With the exponential increase in the number of sequenced organisms, automated annotation of proteins is becoming increasingly important. Intrinsically disordered regions are known to play a significant role in protein function. Despite their abundance, especially in eukaryotes, they are rarely used to inform function prediction systems. In this study, we extracted seven sequence features in intrinsically disordered regions and developed a scheme to use them to predict Gene Ontology Slim terms associated with proteins. We evaluated the function prediction performance of each feature. Our results indicate that the residue composition based features have the highest precision while bigram probabilities, based on sequence profiles of intrinsically disordered regions obtained from PSIBlast, have the highest recall. Amino acid bigrams and features based on secondary structure show an intermediate level of precision and recall. Almost all features showed a high prediction performance for GO Slim terms related to extracellular matrix, nucleus, RNA and DNA binding. However, feature performance varied significantly for different GO Slim terms emphasizing the need for a unique classifier optimized for the prediction of each functional term. These findings provide a first comprehensive and quantitative evaluation of sequence features in intrinsically disordered regions and will help in the development of a more informative protein function predictor.Alok SharmaAbdollah DehzangiJames LyonsSeiya ImotoSatoru MiyanoKenta NakaiAshwini PatilPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 2, p e89890 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Alok Sharma Abdollah Dehzangi James Lyons Seiya Imoto Satoru Miyano Kenta Nakai Ashwini Patil Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.
description	With the exponential increase in the number of sequenced organisms, automated annotation of proteins is becoming increasingly important. Intrinsically disordered regions are known to play a significant role in protein function. Despite their abundance, especially in eukaryotes, they are rarely used to inform function prediction systems. In this study, we extracted seven sequence features in intrinsically disordered regions and developed a scheme to use them to predict Gene Ontology Slim terms associated with proteins. We evaluated the function prediction performance of each feature. Our results indicate that the residue composition based features have the highest precision while bigram probabilities, based on sequence profiles of intrinsically disordered regions obtained from PSIBlast, have the highest recall. Amino acid bigrams and features based on secondary structure show an intermediate level of precision and recall. Almost all features showed a high prediction performance for GO Slim terms related to extracellular matrix, nucleus, RNA and DNA binding. However, feature performance varied significantly for different GO Slim terms emphasizing the need for a unique classifier optimized for the prediction of each functional term. These findings provide a first comprehensive and quantitative evaluation of sequence features in intrinsically disordered regions and will help in the development of a more informative protein function predictor.
format	article
author	Alok Sharma Abdollah Dehzangi James Lyons Seiya Imoto Satoru Miyano Kenta Nakai Ashwini Patil
author_facet	Alok Sharma Abdollah Dehzangi James Lyons Seiya Imoto Satoru Miyano Kenta Nakai Ashwini Patil
author_sort	Alok Sharma
title	Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.
title_short	Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.
title_full	Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.
title_fullStr	Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.
title_full_unstemmed	Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.
title_sort	evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/524d9657344049c3aeef6794bb47771b
work_keys_str_mv	AT aloksharma evaluationofsequencefeaturesfromintrinsicallydisorderedregionsfortheestimationofproteinfunction AT abdollahdehzangi evaluationofsequencefeaturesfromintrinsicallydisorderedregionsfortheestimationofproteinfunction AT jameslyons evaluationofsequencefeaturesfromintrinsicallydisorderedregionsfortheestimationofproteinfunction AT seiyaimoto evaluationofsequencefeaturesfromintrinsicallydisorderedregionsfortheestimationofproteinfunction AT satorumiyano evaluationofsequencefeaturesfromintrinsicallydisorderedregionsfortheestimationofproteinfunction AT kentanakai evaluationofsequencefeaturesfromintrinsicallydisorderedregionsfortheestimationofproteinfunction AT ashwinipatil evaluationofsequencefeaturesfromintrinsicallydisorderedregionsfortheestimationofproteinfunction
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Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.

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