DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.

<h4>Motivation</h4>The precise prediction of protein domains, which are the structural, functional and evolutionary units of proteins, has been a research focus in recent years. Although many methods have been presented for predicting protein domains and boundaries, the accuracy of predi...

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Autores principales:	Xiao-yan Zhang, Long-jian Lu, Qi Song, Qian-qian Yang, Da-peng Li, Jiang-ming Sun, Tong-hua Li, Pei-sheng Cong
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/738f2c10fc8d443db69807c9c2fc54b5
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spelling	oai:doaj.org-article:738f2c10fc8d443db69807c9c2fc54b52021-11-18T07:49:47ZDomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.1932-620310.1371/journal.pone.0060559https://doaj.org/article/738f2c10fc8d443db69807c9c2fc54b52013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23593247/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Motivation</h4>The precise prediction of protein domains, which are the structural, functional and evolutionary units of proteins, has been a research focus in recent years. Although many methods have been presented for predicting protein domains and boundaries, the accuracy of predictions could be improved.<h4>Results</h4>In this study we present a novel approach, DomHR, which is an accurate predictor of protein domain boundaries based on a creative hinge region strategy. A hinge region was defined as a segment of amino acids that covers part of a domain region and a boundary region. We developed a strategy to construct profiles of domain-hinge-boundary (DHB) features generated by sequence-domain/hinge/boundary alignment against a database of known domain structures. The DHB features had three elements: normalized domain, hinge, and boundary probabilities. The DHB features were used as input to identify domain boundaries in a sequence. DomHR used a nonredundant dataset as the training set, the DHB and predicted shape string as features, and a conditional random field as the classification algorithm. In predicted hinge regions, a residue was determined to be a domain or a boundary according to a decision threshold. After decision thresholds were optimized, DomHR was evaluated by cross-validation, large-scale prediction, independent test and CASP (Critical Assessment of Techniques for Protein Structure Prediction) tests. All results confirmed that DomHR outperformed other well-established, publicly available domain boundary predictors for prediction accuracy.<h4>Availability</h4>The DomHR is available at http://cal.tongji.edu.cn/domain/.Xiao-yan ZhangLong-jian LuQi SongQian-qian YangDa-peng LiJiang-ming SunTong-hua LiPei-sheng CongPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 4, p e60559 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiao-yan Zhang Long-jian Lu Qi Song Qian-qian Yang Da-peng Li Jiang-ming Sun Tong-hua Li Pei-sheng Cong DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.
description	<h4>Motivation</h4>The precise prediction of protein domains, which are the structural, functional and evolutionary units of proteins, has been a research focus in recent years. Although many methods have been presented for predicting protein domains and boundaries, the accuracy of predictions could be improved.<h4>Results</h4>In this study we present a novel approach, DomHR, which is an accurate predictor of protein domain boundaries based on a creative hinge region strategy. A hinge region was defined as a segment of amino acids that covers part of a domain region and a boundary region. We developed a strategy to construct profiles of domain-hinge-boundary (DHB) features generated by sequence-domain/hinge/boundary alignment against a database of known domain structures. The DHB features had three elements: normalized domain, hinge, and boundary probabilities. The DHB features were used as input to identify domain boundaries in a sequence. DomHR used a nonredundant dataset as the training set, the DHB and predicted shape string as features, and a conditional random field as the classification algorithm. In predicted hinge regions, a residue was determined to be a domain or a boundary according to a decision threshold. After decision thresholds were optimized, DomHR was evaluated by cross-validation, large-scale prediction, independent test and CASP (Critical Assessment of Techniques for Protein Structure Prediction) tests. All results confirmed that DomHR outperformed other well-established, publicly available domain boundary predictors for prediction accuracy.<h4>Availability</h4>The DomHR is available at http://cal.tongji.edu.cn/domain/.
format	article
author	Xiao-yan Zhang Long-jian Lu Qi Song Qian-qian Yang Da-peng Li Jiang-ming Sun Tong-hua Li Pei-sheng Cong
author_facet	Xiao-yan Zhang Long-jian Lu Qi Song Qian-qian Yang Da-peng Li Jiang-ming Sun Tong-hua Li Pei-sheng Cong
author_sort	Xiao-yan Zhang
title	DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.
title_short	DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.
title_full	DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.
title_fullStr	DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.
title_full_unstemmed	DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.
title_sort	domhr: accurately identifying domain boundaries in proteins using a hinge region strategy.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/738f2c10fc8d443db69807c9c2fc54b5
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DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.

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