Exploiting polypharmacology for drug target deconvolution
Exploiting polypharmacology for drug target deconvolution
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DOI：
10.1073/pnas.1403080111
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发表时间：
2014-04-01
影响因子：
11.1
通讯作者：
Kirschner, Marc W.
中科院分区：
文献类型：
--
作者：
Gujral, Taranjit Singh;Peshkin, Leonid;Kirschner, Marc W.
多药理学（药物对多个靶点的作用）代表了新药开发的诱人途径;不幸的是，缺乏能够利用已知的药物多药理学进行靶点去卷积的方法。在这里，我们提出了一个集成的方法，使用弹性网络正则化结合mRNA表达谱和以前的特征数据的一大组激酶抑制剂，以确定激酶是重要的上皮细胞和间充质细胞迁移。通过分析一组选定的32种激酶抑制剂对6种细胞系的最佳组合，我们确定了调节细胞迁移的细胞类型特异性激酶。我们发现的几个信息激酶与以前未表征的作用，在细胞迁移（如Mst和Taok家族的MAPK激酶在间充质细胞）可能代表新的目标，值得进一步研究。使用我们的集成方法的目标去卷积有可能帮助更有效，但毒性较小的药物组合的合理设计。
Polypharmacology (action of drugs against multiple targets) represents a tempting avenue for new drug development; unfortunately, methods capable of exploiting the known polypharmacology of drugs for target deconvolution are lacking. Here, we present an ensemble approach using elastic net regularization combined with mRNA expression profiling and previously characterized data on a large set of kinase inhibitors to identify kinases that are important for epithelial and mesenchymal cell migration. By profiling a selected optimal set of 32 kinase inhibitors in a panel against six cell lines, we identified cell type-specific kinases that regulate cell migration. Our discovery of several informative kinases with a previously uncharacterized role in cell migration (such as Mst and Taok family of MAPK kinases in mesenchymal cells) may represent novel targets that warrant further investigation. Target deconvolution using our ensemble approach has the potential to aid in the rational design of more potent but less toxic drug combinations.