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A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks
Large-scale data sets of protein-protein interactions (PPIs) are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in thi...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2827538/ https://www.ncbi.nlm.nih.gov/pubmed/20195357 http://dx.doi.org/10.1371/journal.pone.0009289 |
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author | Miyamoto-Sato, Etsuko Fujimori, Shigeo Ishizaka, Masamichi Hirai, Naoya Masuoka, Kazuyo Saito, Rintaro Ozawa, Yosuke Hino, Katsuya Washio, Takanori Tomita, Masaru Yamashita, Tatsuhiro Oshikubo, Tomohiro Akasaka, Hidetoshi Sugiyama, Jun Matsumoto, Yasuo Yanagawa, Hiroshi |
author_facet | Miyamoto-Sato, Etsuko Fujimori, Shigeo Ishizaka, Masamichi Hirai, Naoya Masuoka, Kazuyo Saito, Rintaro Ozawa, Yosuke Hino, Katsuya Washio, Takanori Tomita, Masaru Yamashita, Tatsuhiro Oshikubo, Tomohiro Akasaka, Hidetoshi Sugiyama, Jun Matsumoto, Yasuo Yanagawa, Hiroshi |
author_sort | Miyamoto-Sato, Etsuko |
collection | PubMed |
description | Large-scale data sets of protein-protein interactions (PPIs) are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in this study also include the sequences involved in the interactions (i.e., the interacting regions, IRs) suggested to correspond to functional and structural domains. Here we present the first large-scale IR data set obtained using mRNA display for 50 human transcription factors (TFs), including 12 transcription-related proteins. The core data set (966 IRs; 943 PPIs) displays a verification rate of 70%. Analysis of the IR data set revealed the existence of IRs that interact with multiple partners. Furthermore, these IRs were preferentially associated with intrinsic disorder. This finding supports the hypothesis that intrinsically disordered regions play a major role in the dynamics and diversity of TF networks through their ability to structurally adapt to and bind with multiple partners. Accordingly, this domain-based interaction resource represents an important step in refining protein interactions and networks at the domain level and in associating network analysis with biological structure and function. |
format | Text |
id | pubmed-2827538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28275382010-03-02 A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks Miyamoto-Sato, Etsuko Fujimori, Shigeo Ishizaka, Masamichi Hirai, Naoya Masuoka, Kazuyo Saito, Rintaro Ozawa, Yosuke Hino, Katsuya Washio, Takanori Tomita, Masaru Yamashita, Tatsuhiro Oshikubo, Tomohiro Akasaka, Hidetoshi Sugiyama, Jun Matsumoto, Yasuo Yanagawa, Hiroshi PLoS One Research Article Large-scale data sets of protein-protein interactions (PPIs) are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in this study also include the sequences involved in the interactions (i.e., the interacting regions, IRs) suggested to correspond to functional and structural domains. Here we present the first large-scale IR data set obtained using mRNA display for 50 human transcription factors (TFs), including 12 transcription-related proteins. The core data set (966 IRs; 943 PPIs) displays a verification rate of 70%. Analysis of the IR data set revealed the existence of IRs that interact with multiple partners. Furthermore, these IRs were preferentially associated with intrinsic disorder. This finding supports the hypothesis that intrinsically disordered regions play a major role in the dynamics and diversity of TF networks through their ability to structurally adapt to and bind with multiple partners. Accordingly, this domain-based interaction resource represents an important step in refining protein interactions and networks at the domain level and in associating network analysis with biological structure and function. Public Library of Science 2010-02-24 /pmc/articles/PMC2827538/ /pubmed/20195357 http://dx.doi.org/10.1371/journal.pone.0009289 Text en Miyamoto-Sato et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Miyamoto-Sato, Etsuko Fujimori, Shigeo Ishizaka, Masamichi Hirai, Naoya Masuoka, Kazuyo Saito, Rintaro Ozawa, Yosuke Hino, Katsuya Washio, Takanori Tomita, Masaru Yamashita, Tatsuhiro Oshikubo, Tomohiro Akasaka, Hidetoshi Sugiyama, Jun Matsumoto, Yasuo Yanagawa, Hiroshi A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks |
title | A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks |
title_full | A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks |
title_fullStr | A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks |
title_full_unstemmed | A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks |
title_short | A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks |
title_sort | comprehensive resource of interacting protein regions for refining human transcription factor networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2827538/ https://www.ncbi.nlm.nih.gov/pubmed/20195357 http://dx.doi.org/10.1371/journal.pone.0009289 |
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