Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery

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dc.contributor.authorFadhal, Emad
dc.contributor.authorMwambene, Eric C
dc.contributor.authorGamieldien, Junaid
dc.date.accessioned2023-02-09T08:22:58Z
dc.date.available2023-02-09T08:22:58Z
dc.date.issued2014
dc.description.abstractWe 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. 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.en_US
dc.identifier.citationFadhal, E. et al. (2014). Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery. BMC Systems Biology, 8, 68. https://doi.org/10.1186/1752-0509-8-68en_US
dc.identifier.issn1752-0509
dc.identifier.urihttps://doi.org/10.1186/1752-0509-8-68
dc.identifier.urihttp://hdl.handle.net/10566/8390
dc.language.isoenen_US
dc.publisherBMCen_US
dc.subjectProtein and nutritionen_US
dc.subjectCanceren_US
dc.subjectPublic healthen_US
dc.subjectDiversityen_US
dc.subjectBioinformaticsen_US
dc.titleModelling human protein interaction networks as metric spaces has potential in disease research and drug target discoveryen_US
dc.typeArticleen_US

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