A causal relationship discovery-based approach to identifying active components of herbal medicine.
Herbal medicine is widely applied for clinical use in East Asia and other countries. However, unclear correlation between its complex chemical composition and bioactivity prevents its application in the West. In the present study, a stepwise causal adjacent relationship discovery algorithm has been developed to study correlation between composition and bioactivity of herbal medicine and identify active components from the complex mixture. This approach was successfully applied in discovering active constituents from mixed extracts of Radix Salviae miltiorrhizae and Cortex Moutan. Moreover, advantage of the present approach compared with bioassay-guided isolation was demonstrated by its application on a typical herbal drug. The current work offers a new way to virtually screen active components of herbal medicine, and it might be helpful to accelerate the process of new drug discovery from natural products.
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310027, China. chengyy@zju.edu.cn
Yiyu
Y
Cheng
Yi
Y
Wang
Xuewei
X
Wang
D000465:Algorithms; D019295:Computational Biology; D015195:Drug Design; D004365:Drugs, Chinese Herbal / Q000737:chemistry* / Q000627:therapeutic use; D006801:Humans; D000960:Hypolipidemic Agents / Q000737:chemistry / Q000627:therapeutic use; D008055:Lipids / Q000097:blood; D008517:Phytotherapy; D010946:Plants, Medicinal / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship
D004365:Drugs, Chinese Herbal; D000960:Hypolipidemic Agents; D008055:Lipids