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Functional site prediction selects correct protein models
BACKGROUND: The prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites. Without this information it is still possible to predict which residues are likely to be part of a functional site and this information can be used to select model s...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2259414/ https://www.ncbi.nlm.nih.gov/pubmed/18315844 http://dx.doi.org/10.1186/1471-2105-9-S1-S13 |
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author | Chelliah, Vijayalakshmi Taylor, William R |
author_facet | Chelliah, Vijayalakshmi Taylor, William R |
author_sort | Chelliah, Vijayalakshmi |
collection | PubMed |
description | BACKGROUND: The prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites. Without this information it is still possible to predict which residues are likely to be part of a functional site and this information can be used to select model structures from a variety of alternatives that would correspond to a functional protein. RESULTS: Using a large collection of protein-like decoy models, a score was devised that selected those with predicted functional site residues that formed a cluster. When tested on a variety of small α/β/α type proteins, including enzymes and non-enzymes, those that corresponded to the native fold were ranked highly. This performance held also for a selection of larger α/β/α proteins that played no part in the development of the method. CONCLUSION: The use of predicted site positions provides a useful filter to discriminate native-like protein models from non-native models. The method can be applied to any collection of models and should provide a useful aid to all modelling methods from ab initio to homology based approaches. |
format | Text |
id | pubmed-2259414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-22594142008-03-04 Functional site prediction selects correct protein models Chelliah, Vijayalakshmi Taylor, William R BMC Bioinformatics Proceedings BACKGROUND: The prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites. Without this information it is still possible to predict which residues are likely to be part of a functional site and this information can be used to select model structures from a variety of alternatives that would correspond to a functional protein. RESULTS: Using a large collection of protein-like decoy models, a score was devised that selected those with predicted functional site residues that formed a cluster. When tested on a variety of small α/β/α type proteins, including enzymes and non-enzymes, those that corresponded to the native fold were ranked highly. This performance held also for a selection of larger α/β/α proteins that played no part in the development of the method. CONCLUSION: The use of predicted site positions provides a useful filter to discriminate native-like protein models from non-native models. The method can be applied to any collection of models and should provide a useful aid to all modelling methods from ab initio to homology based approaches. BioMed Central 2008-02-13 /pmc/articles/PMC2259414/ /pubmed/18315844 http://dx.doi.org/10.1186/1471-2105-9-S1-S13 Text en Copyright © 2008 Chelliah and Taylor; 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 Chelliah, Vijayalakshmi Taylor, William R Functional site prediction selects correct protein models |
title | Functional site prediction selects correct protein models |
title_full | Functional site prediction selects correct protein models |
title_fullStr | Functional site prediction selects correct protein models |
title_full_unstemmed | Functional site prediction selects correct protein models |
title_short | Functional site prediction selects correct protein models |
title_sort | functional site prediction selects correct protein models |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2259414/ https://www.ncbi.nlm.nih.gov/pubmed/18315844 http://dx.doi.org/10.1186/1471-2105-9-S1-S13 |
work_keys_str_mv | AT chelliahvijayalakshmi functionalsitepredictionselectscorrectproteinmodels AT taylorwilliamr functionalsitepredictionselectscorrectproteinmodels |