A large-scale computational approach to drug repositioning.
A large-scale computational approach to drug repositioning.
复制标题
药物重新定位的大规模计算方法。
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
Steven J. M. Jones
中科院分区：
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作者：
Yvonne Y. Li;Jianghong An;Steven J. M. Jones
我们开发了一个用于预测蛋白质-小分子相互作用的计算管道，并通过对已知药物靶点和小分子药物的大规模分析将其应用于药物重新定位问题。我们的管道结合了正向对接和反向对接，后者是对药物发现中使用的传统对接程序的一种扭曲：不是将许多化合物与特定靶点对接以寻找潜在的抑制剂，而是将一种化合物与许多蛋白质对接以寻找潜在靶点。我们广泛收集了 1,055 种已批准的小分子药物和 1,548 个药物靶点结合袋（代表 78 种独特的人类蛋白质治疗靶点），并使用 ICM 软件进行了大规模对接，以验证我们的方法并预测新型蛋白质-药物相互作用。对于我们数据集中具有已知结构复合物的 37 种已知蛋白质-药物相互作用，所有对接构象均在已解构象的 2.0A 范围内，其中 30 种的对接分数超过了典型的 ICM 分数阈值。在 DrugBank 注释的 237 种已知蛋白质-药物相互作用中，74 种通过了分数阈值，52 种显示药物与另一种蛋白质的对接分数高于其已知靶标的对接分数。这些蛋白质靶点与人类疾病有关，因此发现的新的蛋白质-药物相互作用代表了这些药物的潜在新适应症。我们的结果强调了反向对接方法在识别现有药物潜在新治疗用途方面的前景。
We have developed a computational pipeline for the prediction of protein-small molecule interactions and have applied it to the drug repositioning problem through a large-scale analysis of known drug targets and small molecule drugs. Our pipeline combines forward and inverse docking, the latter of which is a twist on the conventional docking procedure used in drug discovery: instead of docking many compounds against a specific target to look for potential inhibitors, one compound is docked against many proteins to search for potential targets. We collected an extensive set of 1,055 approved small molecule drugs and 1,548 drug target binding pockets (representing 78 unique human protein therapeutic targets) and performed a large-scale docking using ICM software to both validate our method and predict novel protein-drug interactions. For the 37 known protein-drug interactions in our data set that have a known structure complex, all docked conformations were within 2.0A of the solved conformation, and 30 of these had a docking score passing the typical ICM score threshold. Out of the 237 known protein-drug interactions annotated by DrugBank, 74 passed the score threshold, and 52 showed the drug docking to another protein with a better docking score than to its known target. These protein targets are implicated in human diseases, so novel protein-drug interactions discovered represent potential novel indications for the drugs. Our results highlight the promising nature of the inverse docking method for identifying potential novel therapeutic uses for existing drugs.