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K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores
BACKGROUND: Network biology currently focuses primarily on metabolic pathways, gene regulatory, and protein-protein interaction networks. While these approaches have yielded critical information, alternative methods to network analysis will offer new perspectives on biological information. A little...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4357223/ https://www.ncbi.nlm.nih.gov/pubmed/25767694 http://dx.doi.org/10.1186/s13336-015-0016-6 |
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author | Emerson, Arnold I Andrews, Simeon Ahmed, Ikhlak Azis, Thasni KA Malek, Joel A |
author_facet | Emerson, Arnold I Andrews, Simeon Ahmed, Ikhlak Azis, Thasni KA Malek, Joel A |
author_sort | Emerson, Arnold I |
collection | PubMed |
description | BACKGROUND: Network biology currently focuses primarily on metabolic pathways, gene regulatory, and protein-protein interaction networks. While these approaches have yielded critical information, alternative methods to network analysis will offer new perspectives on biological information. A little explored area is the interactions between domains that can be captured using domain co-occurrence networks (DCN). A DCN can be used to study the function and interaction of proteins by representing protein domains and their co-existence in genes and by mapping cancer mutations to the individual protein domains to identify signals. RESULTS: The domain co-occurrence network was constructed for the human proteome based on PFAM domains in proteins. Highly connected domains in the central cores were identified using the k-core decomposition technique. Here we show that these domains were found to be more evolutionarily conserved than the peripheral domains. The somatic mutations for ovarian, breast and prostate cancer diseases were obtained from the TCGA database. We mapped the somatic mutations to the individual protein domains and the local false discovery rate was used to identify significantly mutated domains in each cancer type. Significantly mutated domains were found to be enriched in cancer disease pathways. However, we found that the inner cores of the DCN did not contain any of the significantly mutated domains. We observed that the inner core protein domains are highly conserved and these domains co-exist in large numbers with other protein domains. CONCLUSION: Mutations and domain co-occurrence networks provide a framework for understanding hierarchal designs in protein function from a network perspective. This study provides evidence that a majority of protein domains in the inner core of the DCN have a lower mutation frequency and that protein domains present in the peripheral regions of the k-core contribute more heavily to the disease. These findings may contribute further to drug development. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13336-015-0016-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4357223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43572232015-03-13 K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores Emerson, Arnold I Andrews, Simeon Ahmed, Ikhlak Azis, Thasni KA Malek, Joel A J Clin Bioinforma Research BACKGROUND: Network biology currently focuses primarily on metabolic pathways, gene regulatory, and protein-protein interaction networks. While these approaches have yielded critical information, alternative methods to network analysis will offer new perspectives on biological information. A little explored area is the interactions between domains that can be captured using domain co-occurrence networks (DCN). A DCN can be used to study the function and interaction of proteins by representing protein domains and their co-existence in genes and by mapping cancer mutations to the individual protein domains to identify signals. RESULTS: The domain co-occurrence network was constructed for the human proteome based on PFAM domains in proteins. Highly connected domains in the central cores were identified using the k-core decomposition technique. Here we show that these domains were found to be more evolutionarily conserved than the peripheral domains. The somatic mutations for ovarian, breast and prostate cancer diseases were obtained from the TCGA database. We mapped the somatic mutations to the individual protein domains and the local false discovery rate was used to identify significantly mutated domains in each cancer type. Significantly mutated domains were found to be enriched in cancer disease pathways. However, we found that the inner cores of the DCN did not contain any of the significantly mutated domains. We observed that the inner core protein domains are highly conserved and these domains co-exist in large numbers with other protein domains. CONCLUSION: Mutations and domain co-occurrence networks provide a framework for understanding hierarchal designs in protein function from a network perspective. This study provides evidence that a majority of protein domains in the inner core of the DCN have a lower mutation frequency and that protein domains present in the peripheral regions of the k-core contribute more heavily to the disease. These findings may contribute further to drug development. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13336-015-0016-6) contains supplementary material, which is available to authorized users. BioMed Central 2015-03-03 /pmc/articles/PMC4357223/ /pubmed/25767694 http://dx.doi.org/10.1186/s13336-015-0016-6 Text en © Emerson et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Emerson, Arnold I Andrews, Simeon Ahmed, Ikhlak Azis, Thasni KA Malek, Joel A K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores |
title | K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores |
title_full | K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores |
title_fullStr | K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores |
title_full_unstemmed | K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores |
title_short | K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores |
title_sort | k-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4357223/ https://www.ncbi.nlm.nih.gov/pubmed/25767694 http://dx.doi.org/10.1186/s13336-015-0016-6 |
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