期刊
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
卷 29, 期 1, 页码 38-45出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmgm.2010.04.007
关键词
Natural product; Structural activity relationship; Bioactive natural compound-likeness; Drug-likeness; Statistical learning
类别
资金
- National Natural Science Foundation of China (NSFC) [30970690]
- Zhejiang Provincial Natural Science Foundation of China [R207609]
Natural products (NPs) have been widely used in traditional medicines and are a valuable source for new drug discovery. However, insufficient knowledge about their molecular mechanisms has limited the scope of their application and hindered the effort to design new drugs from their synergistic action strategies. Thus far, a systematic study of all NP ingredients in a traditional medicine recipe remains impractical. However encouraging results have begun to appear illustrating synergies between several principle active ingredients. In this work, we propose the use of structure activity relationship (SAR) to identify potential active ingredients in natural products, with the aim to facilitate experimental and computational characterizations of their therapeutic mechanisms and synergies. We call this approach the bioactive natural compound-likeness (BNC-likeness) approach, drawing a parallel to the concept of drug-likeness. In cross-validations and independent example tests, our approach displayed 90-92% sensitivity and 85-90% specificity, suggesting its practical usefulness. We also showed that BNC-like compounds were not just drug-like NP ingredients. BNC-like compounds and drug-like chemicals may share different structural characteristics. Therefore, BNC-likeness is a helpful novel conception inviting dedicated research. (C) 2010 Elsevier Inc. All rights reserved.
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