Discovering active compounds from mixture of natural products by data mining approach.
Traditionally, active compounds were discovered from natural products by repeated isolation and bioassays, which can be highly time consuming. Here, we have developed a data mining approach using the casual discovery algorithm to identify active compounds from mixtures by investigating the correlation between their chemical composition and bioactivity in the mixtures. The efficacy of our algorithm was validated by the cytotoxic effect of Panax ginseng extracts on MCF-7 cells and compared with previous reports. It was demonstrated that our method could successfully pick out active compounds from a mixture in the absence of separation processes. It is expected that the presented algorithm can possibly accelerate the process of discovering new drugs.
Wang
Yi
Y
Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, 310058, Hangzhou, China.
Jin
Yecheng
Y
Zhou
Chenguang
C
Qu
Haibin
H
Cheng
Yiyu
Y
D000465:Algorithms; D001681:Biological Assay; D001688:Biological Products / Q000737:chemistry* / Q000627:therapeutic use; D019295:Computational Biology; D015195:Drug Design; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D015394:Molecular Structure; D013329:Structure-Activity Relationship
D001688:Biological Products