Predicting effective drug combinations via network propagation
Predicting effective drug combinations via network propagation
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DOI：
10.1109/biocas.2013.6679718
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发表时间：
2013-12
期刊：
影响因子：
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通讯作者：
B. Ligeti;Roberto Vera;Gergely Lukács;Balázs Győrffy;S. Pongor
中科院分区：
文献类型：
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作者：
B. Ligeti;Roberto Vera;Gergely Lukács;Balázs Győrffy;S. Pongor
药物组合经常用于治疗复杂的疾病，包括癌症、糖尿病、关节炎和高血压。大多数药物组合都是以经验方式发现的，因此需要有效的计算方法。在这里，我们提出了一种基于网络分析的新方法，该方法通过在蛋白质-蛋白质关联网络上进行的扰动分析来估计药物组合的功效。结果表明，这些药物很可能形成有效的组合，扰乱大量共同的蛋白质，即使最初的靶标是在看似不相关的途径中发现的。
Drug combinations are frequently used in treating complex diseases including cancer, diabetes, arthritis and hypertension. Most drug combinations were found in empirical ways so there is a need of efficient computational methods. Here we present a novel method based on network analysis which estimates the efficacy of drug combinations from a perturbation analysis performed on a protein-protein association network. The results suggest that those drugs are likely to form effective combinations that perturb a large number of proteins in common, even if the original targets are found in seemingly unrelated pathways.