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整合系统生物学资源阐明药物作用。

Integrating systems biology sources illuminates drug action.

机构信息

Department of Genetics, Stanford University, Stanford, California, USA.

1] Department of Genetics, Stanford University, Stanford, California, USA [2] Department of Bioengineering, Stanford University, Stanford, California, USA.

出版信息

Clin Pharmacol Ther. 2014 Jun;95(6):663-9. doi: 10.1038/clpt.2014.51. Epub 2014 Feb 27.

Abstract

There are significant gaps in our understanding of the pathways by which drugs act. This incomplete knowledge limits our ability to use mechanistic molecular information rationally to repurpose drugs, understand their side effects, and predict their interactions with other drugs. Here, we present DrugRouter, a novel method for generating drug-specific pathways of action by linking target genes, disease genes, and pharmacogenes using gene interaction networks. We construct pathways for more than a hundred drugs and show that the genes included in our pathways (i) co-occur with the query drug in the literature, (ii) significantly overlap or are adjacent to known drug-response pathways, and (iii) are adjacent to genes that are hits in genome-wide association studies assessing drug response. Finally, these computed pathways suggest novel drug-repositioning opportunities (e.g., statins for follicular thyroid cancer), gene-side effect associations, and gene-drug interactions. Thus, DrugRouter generates hypotheses about drug actions using systems biology data.

摘要

我们对药物作用途径的理解存在很大差距。这种不完全的知识限制了我们合理利用机制分子信息来重新利用药物、了解其副作用以及预测它们与其他药物的相互作用的能力。在这里,我们提出了 DrugRouter,这是一种通过使用基因相互作用网络将靶基因、疾病基因和药理基因联系起来生成特定药物作用途径的新方法。我们为一百多种药物构建了途径,并表明我们途径中包含的基因:(i)在文献中与查询药物共同出现,(ii)与已知的药物反应途径显著重叠或相邻,(iii)与评估药物反应的全基因组关联研究中的命中基因相邻。最后,这些计算出的途径提示了新的药物重新定位机会(例如,他汀类药物用于滤泡性甲状腺癌)、基因-副作用关联和基因-药物相互作用。因此,DrugRouter 使用系统生物学数据生成关于药物作用的假设。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af26/4029855/f1929092113c/nihms572627f1.jpg

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