Robust ligand-based modeling of the biological targets of known drugs
Robust ligand-based modeling of the biological targets of known drugs
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DOI：
10.1021/jm051139t
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发表时间：
2006-05-18
影响因子：
7.3
通讯作者：
Jain, Ajay N.
中科院分区：
文献类型：
--
作者：
Cleves, Ann E.;Jain, Ajay N.
对大约1000种已知疗法的主要靶点的系统注释揭示，其中超过700种调节大约85种生物靶点。我们报告了三个分析的结果。在第一个分析中，药物/药物相似性和目标/目标相似性的基础上计算的三维配体结构。共享靶标的药物对比不共享靶标的药物对具有显著更高的相似性。此外，在注释的药物特异性中没有重叠的靶对比具有增加的重叠的靶对共享更低的相似性。药物和靶点的双向凝聚聚类与已知的药理学一致，并提示可能通过模拟许多靶点来揭示副作用和药物-药物相互作用。在第二个分析中，我们使用筛选分子的背景在虚拟屏幕中构建并测试了22个不同靶标的基于配体的模型。在20/22例病例中观察到同源分子相对于随机分子富集超过100倍。在第三次分析中，使用药物分子背景测试模型的选择性，在17/22例病例中观察到大于80倍的选择性。预测活动来自交叉药物对建模的目标确定了一些已知的副作用，药物特异性，药物相互作用，具有合理的分子结构的基础。
Systematic annotation of the primary targets of roughly 1000 known therapeutics reveals that over 700 of these modulate approximately 85 biological targets. We report the results of three analyses. In the first analysis, drug/drug similarities and target/target similarities were computed on the basis of three-dimensional ligand structures. Drug pairs sharing a target had significantly higher similarity than drug pairs sharing no target. Also, target pairs with no overlap in annotated drug specificity shared lower similarity than target pairs with increasing overlap. Two-way agglomerative clusterings of drugs and targets were consistent with known pharmacology and suggestive that side effects and drug-drug interactions might be revealed by modeling many targets. In the second analysis, we constructed and tested ligand-based models of 22 diverse targets in virtual screens using a background of screening molecules. Greater than 100-fold enrichment of cognate versus random molecules was observed in 20/22 cases. In the third analysis, selectivity of the models was tested using a background of drug molecules, with selectivity of greater than 80-fold observed in 17/22 cases. Predicted activities derived from crossing drugs against modeled targets identified a number of known side effects, drug specificities, and drug-drug interactions that have a rational basis in molecular structure.