期刊
MEDICINAL CHEMISTRY
卷 8, 期 3, 页码 309-319出版社
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/157340612800786651
关键词
Acridinones; antitumor activity; artificial neural networks (ANNs); molecular descriptors; sensitivity analysis
Artificial neural networks (ANNs) have been applied for the quantitative structure-activity relationships (QSAR) studies of antitumor activity of acridinone derivatives. Molecular modeling studies were performed with the use of HyperChem and Dragon computer programs and molecular geometry optimization using MM+ molecular mechanics and semi-empirical AM1 method, and several molecular descriptors of agents were obtained. A high correlation resulted between the ANN predicted antitumor activity and that one from biological experiments for the data used in the testing set of acridinones was obtained with correlation coefficient on the level of 0.9484. Moreover, the sensitivity analysis indicated that molecular parameters describing geometrical properties as well as lipophilicity of acridinone derivative molecule are important for acridinones antitumor activity.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据