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Structure-based prediction of C(2)H(2) zinc-finger binding specificity: sensitivity to docking geometry
Predicting the binding specificity of transcription factors is a critical step in the characterization and computational identification and of cis-regulatory elements in genomic sequences. Here we use protein–DNA structures to predict binding specificity and consider the possibility of predicting po...
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Formato: | Texto |
Lenguaje: | English |
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Oxford University Press
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1851644/ https://www.ncbi.nlm.nih.gov/pubmed/17264128 http://dx.doi.org/10.1093/nar/gkl1155 |
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author | Siggers, Trevor W. Honig, Barry |
author_facet | Siggers, Trevor W. Honig, Barry |
author_sort | Siggers, Trevor W. |
collection | PubMed |
description | Predicting the binding specificity of transcription factors is a critical step in the characterization and computational identification and of cis-regulatory elements in genomic sequences. Here we use protein–DNA structures to predict binding specificity and consider the possibility of predicting position weight matrices (PWM) for an entire protein family based on the structures of just a few family members. A particular focus is the sensitivity of prediction accuracy to the docking geometry of the structure used. We investigate this issue with the goal of determining how similar two docking geometries must be for binding specificity predictions to be accurate. Docking similarity is quantified using our recently described interface alignment score (IAS). Using a molecular-mechanics force field, we predict high-affinity nucleotide sequences that bind to the second zinc-finger (ZF) domain from the Zif268 protein, using different C(2)H(2) ZF domains as structural templates. We identify a strong relationship between IAS values and prediction accuracy, and define a range of IAS values for which accurate structure-based predictions of binding specificity is to be expected. The implication of our results for large-scale, structure-based prediction of PWMs is discussed. |
format | Text |
id | pubmed-1851644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-18516442007-04-26 Structure-based prediction of C(2)H(2) zinc-finger binding specificity: sensitivity to docking geometry Siggers, Trevor W. Honig, Barry Nucleic Acids Res Computational Biology Predicting the binding specificity of transcription factors is a critical step in the characterization and computational identification and of cis-regulatory elements in genomic sequences. Here we use protein–DNA structures to predict binding specificity and consider the possibility of predicting position weight matrices (PWM) for an entire protein family based on the structures of just a few family members. A particular focus is the sensitivity of prediction accuracy to the docking geometry of the structure used. We investigate this issue with the goal of determining how similar two docking geometries must be for binding specificity predictions to be accurate. Docking similarity is quantified using our recently described interface alignment score (IAS). Using a molecular-mechanics force field, we predict high-affinity nucleotide sequences that bind to the second zinc-finger (ZF) domain from the Zif268 protein, using different C(2)H(2) ZF domains as structural templates. We identify a strong relationship between IAS values and prediction accuracy, and define a range of IAS values for which accurate structure-based predictions of binding specificity is to be expected. The implication of our results for large-scale, structure-based prediction of PWMs is discussed. Oxford University Press 2007-02 2007-01-30 /pmc/articles/PMC1851644/ /pubmed/17264128 http://dx.doi.org/10.1093/nar/gkl1155 Text en © 2007 The Author(s). 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 Siggers, Trevor W. Honig, Barry Structure-based prediction of C(2)H(2) zinc-finger binding specificity: sensitivity to docking geometry |
title | Structure-based prediction of C(2)H(2) zinc-finger binding specificity: sensitivity to docking geometry |
title_full | Structure-based prediction of C(2)H(2) zinc-finger binding specificity: sensitivity to docking geometry |
title_fullStr | Structure-based prediction of C(2)H(2) zinc-finger binding specificity: sensitivity to docking geometry |
title_full_unstemmed | Structure-based prediction of C(2)H(2) zinc-finger binding specificity: sensitivity to docking geometry |
title_short | Structure-based prediction of C(2)H(2) zinc-finger binding specificity: sensitivity to docking geometry |
title_sort | structure-based prediction of c(2)h(2) zinc-finger binding specificity: sensitivity to docking geometry |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1851644/ https://www.ncbi.nlm.nih.gov/pubmed/17264128 http://dx.doi.org/10.1093/nar/gkl1155 |
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