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DNA-binding residues and binding mode prediction with binding-mechanism concerned models

BACKGROUND: Protein-DNA interactions are essential for fundamental biological activities including DNA transcription, replication, packaging, repair and rearrangement. Proteins interacting with DNA can be classified into two categories of binding mechanisms - sequence-specific and non-specific bindi...

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Autores principales: Huang, Yu-Feng, Huang, Chun-Chin, Liu, Yu-Cheng, Oyang, Yen-Jen, Huang, Chien-Kang
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788376/
https://www.ncbi.nlm.nih.gov/pubmed/19958487
http://dx.doi.org/10.1186/1471-2164-10-S3-S23
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author Huang, Yu-Feng
Huang, Chun-Chin
Liu, Yu-Cheng
Oyang, Yen-Jen
Huang, Chien-Kang
author_facet Huang, Yu-Feng
Huang, Chun-Chin
Liu, Yu-Cheng
Oyang, Yen-Jen
Huang, Chien-Kang
author_sort Huang, Yu-Feng
collection PubMed
description BACKGROUND: Protein-DNA interactions are essential for fundamental biological activities including DNA transcription, replication, packaging, repair and rearrangement. Proteins interacting with DNA can be classified into two categories of binding mechanisms - sequence-specific and non-specific binding. Protein-DNA specific binding provides a mechanism to recognize correct nucleotide base pairs for sequence-specific identification. Protein-DNA non-specific binding shows sequence independent interaction for accelerated targeting by interacting with DNA backbone. Both sequence-specific and non-specific binding residues contribute to their roles for interaction. RESULTS: The proposed framework has two stage predictors: DNA-binding residues prediction and binding mode prediction. In the first stage - DNA-binding residues prediction, the predictor for DNA specific binding residues achieves 96.45% accuracy with 50.14% sensitivity, 99.31% specificity, 81.70% precision, and 62.15% F-measure. The predictor for DNA non-specific binding residues achieves 89.14% accuracy with 53.06% sensitivity, 95.25% specificity, 65.47% precision, and 58.62% F-measure. While combining prediction results of sequence-specific and non-specific binding residues with OR operation, the predictor achieves 89.26% accuracy with 56.86% sensitivity, 95.63% specificity, 71.92% precision, and 63.51% F-measure. In the second stage, protein-DNA binding mode prediction achieves 75.83% accuracy while using support vector machine with multi-class prediction. CONCLUSION: This article presents the design of a sequence based predictor aiming to identify sequence-specific and non-specific binding residues in a transcription factor with DNA binding-mechanism concerned. The protein-DNA binding mode prediction was introduced to help improve DNA-binding residues prediction. In addition, the results of this study will help with the design of binding-mechanism concerned predictors for other families of proteins interacting with DNA.
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spelling pubmed-27883762009-12-04 DNA-binding residues and binding mode prediction with binding-mechanism concerned models Huang, Yu-Feng Huang, Chun-Chin Liu, Yu-Cheng Oyang, Yen-Jen Huang, Chien-Kang BMC Genomics Proceedings BACKGROUND: Protein-DNA interactions are essential for fundamental biological activities including DNA transcription, replication, packaging, repair and rearrangement. Proteins interacting with DNA can be classified into two categories of binding mechanisms - sequence-specific and non-specific binding. Protein-DNA specific binding provides a mechanism to recognize correct nucleotide base pairs for sequence-specific identification. Protein-DNA non-specific binding shows sequence independent interaction for accelerated targeting by interacting with DNA backbone. Both sequence-specific and non-specific binding residues contribute to their roles for interaction. RESULTS: The proposed framework has two stage predictors: DNA-binding residues prediction and binding mode prediction. In the first stage - DNA-binding residues prediction, the predictor for DNA specific binding residues achieves 96.45% accuracy with 50.14% sensitivity, 99.31% specificity, 81.70% precision, and 62.15% F-measure. The predictor for DNA non-specific binding residues achieves 89.14% accuracy with 53.06% sensitivity, 95.25% specificity, 65.47% precision, and 58.62% F-measure. While combining prediction results of sequence-specific and non-specific binding residues with OR operation, the predictor achieves 89.26% accuracy with 56.86% sensitivity, 95.63% specificity, 71.92% precision, and 63.51% F-measure. In the second stage, protein-DNA binding mode prediction achieves 75.83% accuracy while using support vector machine with multi-class prediction. CONCLUSION: This article presents the design of a sequence based predictor aiming to identify sequence-specific and non-specific binding residues in a transcription factor with DNA binding-mechanism concerned. The protein-DNA binding mode prediction was introduced to help improve DNA-binding residues prediction. In addition, the results of this study will help with the design of binding-mechanism concerned predictors for other families of proteins interacting with DNA. BioMed Central 2009-12-03 /pmc/articles/PMC2788376/ /pubmed/19958487 http://dx.doi.org/10.1186/1471-2164-10-S3-S23 Text en Copyright ©2009 Huang et al; 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
Huang, Yu-Feng
Huang, Chun-Chin
Liu, Yu-Cheng
Oyang, Yen-Jen
Huang, Chien-Kang
DNA-binding residues and binding mode prediction with binding-mechanism concerned models
title DNA-binding residues and binding mode prediction with binding-mechanism concerned models
title_full DNA-binding residues and binding mode prediction with binding-mechanism concerned models
title_fullStr DNA-binding residues and binding mode prediction with binding-mechanism concerned models
title_full_unstemmed DNA-binding residues and binding mode prediction with binding-mechanism concerned models
title_short DNA-binding residues and binding mode prediction with binding-mechanism concerned models
title_sort dna-binding residues and binding mode prediction with binding-mechanism concerned models
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2788376/
https://www.ncbi.nlm.nih.gov/pubmed/19958487
http://dx.doi.org/10.1186/1471-2164-10-S3-S23
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