Artificial neural network applied to prediction of fluorquinolone antibacterial activity by topological methods

被引：35

作者：

Jaén-Oltra, J ^{[1
]}

Salabert-Salvador, T ^{[1
]}

García-March, FJ ^{[1
]}

Pérez-Giménez, F ^{[1
]}

Tomás-Vert, F ^{[1
]}

机构：

[1] Univ Valencia, Dept Chem Phys, E-46100 Valencia, Spain

来源：

JOURNAL OF MEDICINAL CHEMISTRY | 2000年 / 43卷 / 06期

关键词：

D O I：

10.1021/jm980448z

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

A new topological method that makes it possible to predict the properties of molecules on the basis of their chemical structures is applied in the present study to quinolone antimicrobial agents. This method uses neural networks in which training algorithms are used as well as different concepts and methods of artificial intelligence with a suitable set of topological descriptors. This makes it possible to determine the minimal inhibitory concentration (MIC) of quinolones. Analysis of the results shows that the experimental and calculated values are highly similar. It is possible to obtain a QSAR interpretation of the information contained in the network after the training has been carried out.

引用

页码：1143 / 1148

页数：6

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