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Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery
BACKGROUND: We have recently shown by formally modelling human protein interaction networks (PINs) as metric spaces and classified proteins into zones based on their distance from the topological centre that hub proteins are primarily centrally located. We also showed that zones closest to the netwo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4088370/ https://www.ncbi.nlm.nih.gov/pubmed/24929653 http://dx.doi.org/10.1186/1752-0509-8-68 |
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author | Fadhal, Emad Mwambene, Eric C Gamieldien, Junaid |
author_facet | Fadhal, Emad Mwambene, Eric C Gamieldien, Junaid |
author_sort | Fadhal, Emad |
collection | PubMed |
description | BACKGROUND: We have recently shown by formally modelling human protein interaction networks (PINs) as metric spaces and classified proteins into zones based on their distance from the topological centre that hub proteins are primarily centrally located. We also showed that zones closest to the network centre are enriched for critically important proteins and are also functionally very specialised for specific ‘house keeping’ functions. We proposed that proteins closest to the network centre may present good therapeutic targets. Here, we present multiple pieces of novel functional evidence that provides strong support for this hypothesis. RESULTS: We found that the human PINs has a highly connected signalling core, with the majority of proteins involved in signalling located in the two zones closest to the topological centre. The majority of essential, disease related, tumour suppressor, oncogenic and approved drug target proteins were found to be centrally located. Similarly, the majority of proteins consistently expressed in 13 types of cancer are also predominantly located in zones closest to the centre. Proteins from zones 1 and 2 were also found to comprise the majority of proteins in key KEGG pathways such as MAPK-signalling, the cell cycle, apoptosis and also pathways in cancer, with very similar patterns seen in pathways that lead to cancers such as melanoma and glioma, and non-neoplastic diseases such as measles, inflammatory bowel disease and Alzheimer’s disease. CONCLUSIONS: Based on the diversity of evidence uncovered, we propose that when considered holistically, proteins located centrally in the human PINs that also have similar functions to existing drug targets are good candidate targets for novel therapeutics. Similarly, since disease pathways are dominated by centrally located proteins, candidates shortlisted in genome scale disease studies can be further prioritized and contextualised based on whether they occupy central positions in the human PINs. |
format | Online Article Text |
id | pubmed-4088370 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40883702014-07-10 Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery Fadhal, Emad Mwambene, Eric C Gamieldien, Junaid BMC Syst Biol Research Article BACKGROUND: We have recently shown by formally modelling human protein interaction networks (PINs) as metric spaces and classified proteins into zones based on their distance from the topological centre that hub proteins are primarily centrally located. We also showed that zones closest to the network centre are enriched for critically important proteins and are also functionally very specialised for specific ‘house keeping’ functions. We proposed that proteins closest to the network centre may present good therapeutic targets. Here, we present multiple pieces of novel functional evidence that provides strong support for this hypothesis. RESULTS: We found that the human PINs has a highly connected signalling core, with the majority of proteins involved in signalling located in the two zones closest to the topological centre. The majority of essential, disease related, tumour suppressor, oncogenic and approved drug target proteins were found to be centrally located. Similarly, the majority of proteins consistently expressed in 13 types of cancer are also predominantly located in zones closest to the centre. Proteins from zones 1 and 2 were also found to comprise the majority of proteins in key KEGG pathways such as MAPK-signalling, the cell cycle, apoptosis and also pathways in cancer, with very similar patterns seen in pathways that lead to cancers such as melanoma and glioma, and non-neoplastic diseases such as measles, inflammatory bowel disease and Alzheimer’s disease. CONCLUSIONS: Based on the diversity of evidence uncovered, we propose that when considered holistically, proteins located centrally in the human PINs that also have similar functions to existing drug targets are good candidate targets for novel therapeutics. Similarly, since disease pathways are dominated by centrally located proteins, candidates shortlisted in genome scale disease studies can be further prioritized and contextualised based on whether they occupy central positions in the human PINs. BioMed Central 2014-06-14 /pmc/articles/PMC4088370/ /pubmed/24929653 http://dx.doi.org/10.1186/1752-0509-8-68 Text en Copyright © 2014 Fadhal et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 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 Article Fadhal, Emad Mwambene, Eric C Gamieldien, Junaid Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery |
title | Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery |
title_full | Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery |
title_fullStr | Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery |
title_full_unstemmed | Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery |
title_short | Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery |
title_sort | modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4088370/ https://www.ncbi.nlm.nih.gov/pubmed/24929653 http://dx.doi.org/10.1186/1752-0509-8-68 |
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