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

机译:将人类蛋白质相互作用网络建模为度量空间在疾病研究和药物靶标发现方面具有潜力

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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.
机译:背景技术最近,我们已经通过将人类蛋白质相互作用网络(PIN)正式建模为度量空间,并根据蛋白质与中心蛋白主要位于中央的拓扑中心之间的距离,将蛋白质分类为多个区域。我们还表明,最靠近网络中心的区域富含重要蛋白质,并且在功能上也非常专门于特定的“家政服务”功能。我们建议最接近网络中心的蛋白质可能会提出良好的治疗目标。在这里,我们提出了许多新颖的功能证据,为这一假设提供了有力的支持。结果我们发现人PIN具有高度连接的信号转导核心,参与信号转导的大多数蛋白质位于最靠近拓扑中心的两个区域中。发现大多数必需的,与疾病相关的,肿瘤抑制因子,致癌的和批准的药物靶蛋白位于中心。同样,在13种癌症中始终表达的大多数蛋白质也主要位于最靠近中心的区域。还发现来自第1区和第2区的蛋白质包含关键KEGG途径中的大多数蛋白质,例如MAPK信号转导,细胞周期,细胞凋亡以及癌症中的途径,在导致诸如黑色素瘤等癌症的途径中观察到的模式非常相似和神经胶质瘤,以及非肿瘤性疾病,例如麻疹,炎症性肠病和阿尔茨海默氏病。结论基于发现的证据的多样性,我们建议,当从整体上考虑时,位于人PINs中央的蛋白质也具有与现有药物靶标相似的功能,它们是新疗法的良好候选靶标。同样,由于疾病途径主要由位于中心的蛋白质决定,因此可以根据基因组规模疾病研究中入围的候选者是否在人PIN中占据中心位置来进一步确定优先次序和背景。

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