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Identifying foldable regions in protein sequence from the hydrophobic signal
Structural genomics initiatives aim to elucidate representative 3D structures for the majority of protein families over the next decade, but many obstacles must be overcome. The correct design of constructs is extremely important since many proteins will be too large or contain unstructured regions...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2241846/ https://www.ncbi.nlm.nih.gov/pubmed/18056079 http://dx.doi.org/10.1093/nar/gkm1070 |
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author | Pang, Chi N.I. Lin, Kuang Wouters, Merridee A. Heringa, Jaap George, Richard A. |
author_facet | Pang, Chi N.I. Lin, Kuang Wouters, Merridee A. Heringa, Jaap George, Richard A. |
author_sort | Pang, Chi N.I. |
collection | PubMed |
description | Structural genomics initiatives aim to elucidate representative 3D structures for the majority of protein families over the next decade, but many obstacles must be overcome. The correct design of constructs is extremely important since many proteins will be too large or contain unstructured regions and will not be amenable to crystallization. It is therefore essential to identify regions in protein sequences that are likely to be suitable for structural study. Scooby-Domain is a fast and simple method to identify globular domains in protein sequences. Domains are compact units of protein structure and their correct delineation will aid structural elucidation through a divide-and-conquer approach. Scooby-Domain predictions are based on the observed lengths and hydrophobicities of domains from proteins with known tertiary structure. The prediction method employs an A*-search to identify sequence regions that form a globular structure and those that are unstructured. On a test set of 173 proteins with consensus CATH and SCOP domain definitions, Scooby-Domain has a sensitivity of 50% and an accuracy of 29%, which is better than current state-of-the-art methods. The method does not rely on homology searches and, therefore, can identify previously unknown domains. |
format | Text |
id | pubmed-2241846 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-22418462008-02-21 Identifying foldable regions in protein sequence from the hydrophobic signal Pang, Chi N.I. Lin, Kuang Wouters, Merridee A. Heringa, Jaap George, Richard A. Nucleic Acids Res Computational Biology Structural genomics initiatives aim to elucidate representative 3D structures for the majority of protein families over the next decade, but many obstacles must be overcome. The correct design of constructs is extremely important since many proteins will be too large or contain unstructured regions and will not be amenable to crystallization. It is therefore essential to identify regions in protein sequences that are likely to be suitable for structural study. Scooby-Domain is a fast and simple method to identify globular domains in protein sequences. Domains are compact units of protein structure and their correct delineation will aid structural elucidation through a divide-and-conquer approach. Scooby-Domain predictions are based on the observed lengths and hydrophobicities of domains from proteins with known tertiary structure. The prediction method employs an A*-search to identify sequence regions that form a globular structure and those that are unstructured. On a test set of 173 proteins with consensus CATH and SCOP domain definitions, Scooby-Domain has a sensitivity of 50% and an accuracy of 29%, which is better than current state-of-the-art methods. The method does not rely on homology searches and, therefore, can identify previously unknown domains. Oxford University Press 2008-02 2007-12-01 /pmc/articles/PMC2241846/ /pubmed/18056079 http://dx.doi.org/10.1093/nar/gkm1070 Text en © 2007 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Pang, Chi N.I. Lin, Kuang Wouters, Merridee A. Heringa, Jaap George, Richard A. Identifying foldable regions in protein sequence from the hydrophobic signal |
title | Identifying foldable regions in protein sequence from the hydrophobic signal |
title_full | Identifying foldable regions in protein sequence from the hydrophobic signal |
title_fullStr | Identifying foldable regions in protein sequence from the hydrophobic signal |
title_full_unstemmed | Identifying foldable regions in protein sequence from the hydrophobic signal |
title_short | Identifying foldable regions in protein sequence from the hydrophobic signal |
title_sort | identifying foldable regions in protein sequence from the hydrophobic signal |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2241846/ https://www.ncbi.nlm.nih.gov/pubmed/18056079 http://dx.doi.org/10.1093/nar/gkm1070 |
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