Classification of Aurora Kinase inhibitors by Self-Organizing Map and Support Vector Machine

Classification models of Aurora Kinase inhibitors were built using Self-Organizing Map (SOM) and Support Vector Machine (SVM), respectively. The classification models can discriminate the Aurora Kinase inhibitors to three classes: selective inhibitors of Aurora-A kinase, selective inhibitors of Aurora-B kinase and no selectivity. In this study, 10 descriptors were selected to build models. The accuracy of the models in prediction for the training, test sets are 97.0%, 88.9 % for SOM, 95.5% and 100% for SVM, respectively. The SOM and SVM models obtained in this study could be used to for further virtual screening research of selective inhibitors of Aurora-A or Aurora-B kinase.