title: Discovering active compounds from mixture of natural products by data mining approach.
abstract: 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.
authors.affiliation: Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, 310058, Hangzhou, China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Wang
authors.forename: Yecheng
authors.initials: Y
authors.lastname: Jin
authors.forename: Chenguang
authors.initials: C
authors.lastname: Zhou
authors.forename: Haibin
authors.initials: H
authors.lastname: Qu
authors.forename: Yiyu
authors.initials: Y
authors.lastname: Cheng
mesh_terms: 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
chemical_list: D001688:Biological Products