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Predicting specificity-determining residues in two large eukaryotic transcription factor families

Certain amino acid residues in a protein, when mutated, change the protein's function. We present an improved method of finding these specificity-determining positions that uses all the protein sequence data available for a family of homologous proteins. We study in detail two families of eukar...

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Detalles Bibliográficos
Autores principales: Donald, Jason E., Shakhnovich, Eugene I.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1183107/
https://www.ncbi.nlm.nih.gov/pubmed/16085755
http://dx.doi.org/10.1093/nar/gki755
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author Donald, Jason E.
Shakhnovich, Eugene I.
author_facet Donald, Jason E.
Shakhnovich, Eugene I.
author_sort Donald, Jason E.
collection PubMed
description Certain amino acid residues in a protein, when mutated, change the protein's function. We present an improved method of finding these specificity-determining positions that uses all the protein sequence data available for a family of homologous proteins. We study in detail two families of eukaryotic transcription factors, basic leucine zippers and nuclear receptors, because of the large amount of sequences and experimental data available. These protein families also have a clear definition of functional specificity: DNA-binding specificity. We compare our results to three other methods, including the evolutionary trace algorithm and a method that depends on orthology relationships. All of the predictions are compared to the available mutational and crystallographic data. We find that our method provides superior predictions of the known specificity-determining residues and also predicts residue positions within these families that deserve further study for their roles in functional specificity.
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spelling pubmed-11831072005-08-05 Predicting specificity-determining residues in two large eukaryotic transcription factor families Donald, Jason E. Shakhnovich, Eugene I. Nucleic Acids Res Article Certain amino acid residues in a protein, when mutated, change the protein's function. We present an improved method of finding these specificity-determining positions that uses all the protein sequence data available for a family of homologous proteins. We study in detail two families of eukaryotic transcription factors, basic leucine zippers and nuclear receptors, because of the large amount of sequences and experimental data available. These protein families also have a clear definition of functional specificity: DNA-binding specificity. We compare our results to three other methods, including the evolutionary trace algorithm and a method that depends on orthology relationships. All of the predictions are compared to the available mutational and crystallographic data. We find that our method provides superior predictions of the known specificity-determining residues and also predicts residue positions within these families that deserve further study for their roles in functional specificity. Oxford University Press 2005 2005-08-05 /pmc/articles/PMC1183107/ /pubmed/16085755 http://dx.doi.org/10.1093/nar/gki755 Text en © The Author 2005. Published by Oxford University Press. All rights reserved
spellingShingle Article
Donald, Jason E.
Shakhnovich, Eugene I.
Predicting specificity-determining residues in two large eukaryotic transcription factor families
title Predicting specificity-determining residues in two large eukaryotic transcription factor families
title_full Predicting specificity-determining residues in two large eukaryotic transcription factor families
title_fullStr Predicting specificity-determining residues in two large eukaryotic transcription factor families
title_full_unstemmed Predicting specificity-determining residues in two large eukaryotic transcription factor families
title_short Predicting specificity-determining residues in two large eukaryotic transcription factor families
title_sort predicting specificity-determining residues in two large eukaryotic transcription factor families
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1183107/
https://www.ncbi.nlm.nih.gov/pubmed/16085755
http://dx.doi.org/10.1093/nar/gki755
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