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首页> 外文期刊>The Mount Sinai journal of medicine >Network analysis of FDA approved drugs and their targets.
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Network analysis of FDA approved drugs and their targets.

机译:FDA批准药物及其靶标的网络分析。

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The global relationship between drugs that are approved for therapeutic use and the human genome is not known. We employed graph-theory methods to analyze the Federal Food and Drug Administration (FDA) approved drugs and their known molecular targets. We used the FDA Approved Drug Products with Therapeutic Equivalence Evaluations 26(th) Edition Electronic Orange Book (EOB) to identify all FDA approved drugs and their active ingredients. We then connected the list of active ingredients extracted from the EOB to those known human protein targets included in the DrugBank database and constructed a bipartite network. We computed network statistics and conducted Gene Ontology analysis on the drug targets and drug categories. We find that drug to drug-target relationship in the bipartite network is scale-free. Several classes of proteins in the human genome appear to be better targets for drugs since they appear to be selectively enriched as drug targets for the currently FDA approved drugs. These initial observations allow for development of an integrated research methodology to identify general principles of the drug discovery process.
机译:批准用于治疗的药物与人类基因组之间的全局关系尚不清楚。我们采用图论方法分析了美国联邦食品药品监督管理局(FDA)批准的药物及其已知的分子靶标。我们使用了具有治疗等效性评估的FDA批准药品和第26版电子橙皮书(EOB)来识别所有FDA批准的药物及其活性成分。然后,我们将从EOB中提取的活性成分列表与DrugBank数据库中包含的那些已知的人类蛋白质靶标相连,并构建了一个两方网络。我们计算了网络统计数据,并对药物目标和药物类别进行了基因本体分析。我们发现,二方网络中药物与药物-靶标的关系是无标度的。人类基因组中的几种蛋白质似乎是更好的药物靶标,因为它们似乎被选择性地富集为当前FDA批准药物的药物靶标。这些初步观察结果有助于开发综合研究方法,以识别药物发现过程的一般原则。

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