Journal
QSAR & COMBINATORIAL SCIENCE
Volume 28, Issue 9, Pages 989-994Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/qsar.200960008
Keywords
Blood-brain barrier (BBB); Kohonen's self-organizing neural network (KohNN); Support vector machine (SVM); Medicinal chemistry; Drug design
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Funding
- 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
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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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