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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23593247/?tool=EBI |
| _version_ | 1818403971218276352 |
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| 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 |
| collection | DOAJ |
| 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/. |
| first_indexed | 2024-12-14T08:32:44Z |
| format | Article |
| id | doaj.art-738f2c10fc8d443db69807c9c2fc54b5 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-14T08:32:44Z |
| publishDate | 2013-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-738f2c10fc8d443db69807c9c2fc54b52022-12-21T23:09:29ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0184e6055910.1371/journal.pone.0060559DomHR: accurately identifying domain boundaries in proteins using a hinge region strategy.Xiao-yan ZhangLong-jian LuQi SongQian-qian YangDa-peng LiJiang-ming SunTong-hua LiPei-sheng Cong<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/.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23593247/?tool=EBI |
| spellingShingle | 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. PLoS ONE |
| title | 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_short | 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 |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23593247/?tool=EBI |
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