期刊
QSAR & COMBINATORIAL SCIENCE
卷 28, 期 9, 页码 989-994出版社
WILEY-V C H VERLAG GMBH
DOI: 10.1002/qsar.200960008
关键词
Blood-brain barrier (BBB); Kohonen's self-organizing neural network (KohNN); Support vector machine (SVM); Medicinal chemistry; Drug design
类别
资金
- National Natural Science Foundation of China [20605003]
- National High Tech Project [2006AA02Z337]
- SRF for ROCS
- Beijing University of Chemical Technology
- Molecular Networks GmbH, Erlangen, Germany
Kohonen's self-organizing neural network (KohNN) method and support vector machine (SVM) classification method were used to build blood-brain barrier permeation prediction model, respectively. Based on five 2D property autocorrelation descriptors, several models have been built which were able to classify BBB penetration and nonpenetration compounds with the accuracy of over 96%.
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