CNS permeability of drugs predicted by a decision tree

被引：27

作者：

Andres, C ^{[1
]}

Hutter, MC ^{[1
]}

机构：

[1] Univ Saarland, Ctr Bioinformat, D-66041 Saarbrucken, Germany

来源：

QSAR & COMBINATORIAL SCIENCE | 2006年 / 25卷 / 04期

关键词：

ADME; drug design; in silico prediction; semi-empirical molecular orbital method; structure-activity relationship;

D O I：

10.1002/qsar.200510200

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

To predict the ability of drug-like molecules to penetrate the Central Nervous System (CNS), a decision tree was generated. This algorithm was designed to make a straight forward yes/no decision about the permeability of the blood-brain barrier for a given substance, based on the numerical criteria of a large variety of molecular descriptors. The decision tree achieved a prediction accuracy of 96% for the 186 compounds of the training set and 84% for the test set comprising 38 molecules. We found that CNS+drugs are predicted with a higher accuracy (> 94%) than CNS-substances (> 89%).

引用

页码：305 / 309

页数：5

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