期刊
EXPERT OPINION ON DRUG DISCOVERY
卷 6, 期 8, 页码 783-796出版社
TAYLOR & FRANCIS LTD
DOI: 10.1517/17460441.2011.586689
关键词
artificial neural network; BBB penetration; cell membrane permeability; cell-penetrating peptides; gastrointestinal permeation; QSAR
资金
- EU
- Estonian Ministry of Education and Research [SF0140031As09]
Introduction: Membrane-cell penetration is a key property for drug candidates, particularly those related to CNS and gastrointestinal diseases. The ability to know whether a drug or compound has the ability to perform this complex characteristic in advance would save time and money for pharmaceutical companies. One robust and fast solution is to use artificial neural networks (ANNs) to predict the cell penetration of the compound candidates. Areas covered: The authors review the application of ANN methods for ANN modeling in the discovery of cell-penetrating drugs. The article looks at three main systems including the BBB, gastrointestinal absorption and permeation in addition to discussing a new approach for cell-penetrating peptide discovery. This review provides the reader with an overview of the ANN methods and applications for the broader audience interested in prediction of cell penetration of drugs. Expert opinion: ANNs can be successfully applied to the prediction of cell-penetrating drugs. Researchers have a broad field of applications for the use of quantitative structure--activity relationship neural networks in drug discovery and development, and can use these areas to further investigate this important pharmaceutical topic.
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