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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...

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Autores principales: Emerson, Arnold I, Andrews, Simeon, Ahmed, Ikhlak, Azis, Thasni KA, Malek, Joel A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
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.
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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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