...
首页> 外文期刊>BMC Bioinformatics >DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing
【24h】

DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing

机译:DrugGenEx-Net:用于系统药理学和基于基因表达的药物再利用的新型计算平台

获取原文
           

摘要

Background The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) networks and pathway regulation. Results We present a systems polypharmacology platform entitled DrugGenEx-Net (DGE-NET). DGE-NET predicts empirical drug-target (DT) interactions, integrates interaction pairs into a multi-tiered network analysis, and ultimately predicts disease-specific drug polypharmacology through systems-based gene expression analysis. Incorporation of established biological network annotations for protein target-disease, ?signaling pathway, ?molecular function, and protein-protein interactions enhances predicted DT effects on disease pathophysiology. Over 50 drug-disease and 100 drug-pathway predictions are validated. For example, the predicted systems pharmacology of the cholesterol-lowering agent ezetimibe corroborates its potential carcinogenicity. When disease-specific gene expression analysis is integrated, DGE-NET prioritizes known therapeutics/experimental drugs as well as their contra-indications. Proof-of-concept is established for immune-related rheumatoid arthritis and inflammatory bowel disease, as well as neuro-degenerative Alzheimer’s and Parkinson’s diseases. Conclusions DGE-NET is a novel computational method that predicting drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing.
机译:背景技术疾病相关蛋白的靶向对于药物发现很重要,但是基于靶点的发现尚未取得成果。对整个生物学过程进行情境化对于制定成功的药物疾病假说至关重要。网络药理学可通过系统生物学分析(例如蛋白质-蛋白质相互作用(PPI)网络和途径调控)帮助克服基于目标的瓶颈。结果我们提供了一个名为DrugGenEx-Net(DGE-NET)的系统多药理学平台。 DGE-NET可预测经验性药物-靶标(DT)相互作用,将相互作用对整合到多层网络分析中,并最终通过基于系统的基因表达分析来预测特定疾病的药物多药理学。为蛋白质靶标疾病,信号传导途径,分子功能以及蛋白质与蛋白质相互作用建立的已建立的生物网络注释的加入增强了预测的DT对疾病病理生理的影响。验证了超过50种药物疾病和100种药物途径的预测。例如,降胆固醇剂依泽替米贝的预测系统药理学证实了其潜在的致癌性。当整合疾病特异性基因表达分析时,DGE-NET会优先考虑已知的治疗/实验药物及其禁忌症。针对免疫相关类风湿性关节炎和炎性肠病,以及神经退行性阿尔茨海默氏病和帕金森氏病的概念验证已经建立。结论DGE-NET是一种新颖的计算方法,可以通过将系统药理学与基因表达分析进行独特的集成来预测药物治疗和反治疗的适应症。 DGE-NET通过将药物的生物活性与疾病的生物学活性联系在一起,从而正确地预测各种药物疾病的适应症,因此,它是识别候选药物以重新利用的有用方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号