4.7 Article

Classification of Aurora kinase inhibitors by self-organizing map (SOM) and support vector machine (SVM)

Journal

EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
Volume 61, Issue -, Pages 73-83

Publisher

ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ejmech.2012.06.037

Keywords

Aurora kinase inhibitors; Classification models; Self-organizing map (SOM); Support vector machine (SVM); Extended connectivity fingerprints (ECFP_4)

Funding

  1. National Natural Science Foundation of China [20605003, 20975011]
  2. Beijing University of Chemical Technology

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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 (SUM) and Support Vector Machine (SVM). The prediction accuracies of the models (based on the training/test set splitting using SUM 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. (C) 2012 Elsevier Masson SAS. All rights reserved.

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