Yan Aixia, Nie Xianglei, Wang Kai, Wang Maolin
State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, P.O. Box 53, Beijing University of Chemical Technology, 15 BeiSanHuan East Road, Beijing 100029, People's Republic of China.
Eur J Med Chem. 2013 Mar;61:73-83. doi: 10.1016/j.ejmech.2012.06.037. Epub 2012 Jun 26.
The Aurora kinase family (consisting of Aurora-A, -B and -C) is an important group of enzymes that controls several aspects of cell division in mammalian cells. In this study, 512 compounds of Aurora-A and -B inhibitors were collected. They were classified into three classes: dual Aurora-A and Aurora-B inhibitors, selective inhibitors of Aurora-A and selective inhibitors of Aurora-B by Self-Organizing Map (SOM) and Support Vector Machine (SVM). The prediction accuracies of the models (based on the training/test set splitting using SOM method) for the test set were 92.2% for SOM1 and 93.8% for SVM1, respectively. In addition, the extended connectivity fingerprints (ECFP_4) for all the molecules were calculated and structure-activity relationship of Aurora kinase inhibitors was summarized, which may be helpful to find the important structural features of inhibitors relating to the selectivity to Aurora kinases.
极光激酶家族（由极光激酶A、B和C组成）是一类重要的酶，它控制着哺乳动物细胞中细胞分裂的多个方面。在本研究中，收集了512种极光激酶A和B抑制剂化合物。通过自组织映射（SOM）和支持向量机（SVM）将它们分为三类：极光激酶A和B双重抑制剂、极光激酶A选择性抑制剂和极光激酶B选择性抑制剂。（基于使用SOM方法进行训练/测试集划分的）模型对测试集的预测准确率，SOM1为92.2%，SVM1为93.8%。此外，计算了所有分子的扩展连接指纹（ECFP_4），并总结了极光激酶抑制剂的构效关系，这可能有助于找到与极光激酶选择性相关的抑制剂的重要结构特征。
