LAUSR

HIGHLIGHTSUPLC–MS‐based metabolomics and multivariate data analyses were applied for fast identification of anticancer compound(s) in Forsythiae Fructus.Betulinic acid was predicted and experimentally confirmed as the most active anticancer compound in Forsythiae Fructus.The integrated metabolomics analysis could serve as a useful tool for fast identification of active compound(s) in herb extract. ABSTRACT An herb commonly contains hundreds of constituents. Identification of bioactive compound(s) in each herb using conventional approaches is usually inefficient and eco‐unfriendly. In this study, we aimed to fast identify anticancer compounds in Forsythiae Fructus using UPLC/MS‐based metabolomics analysis. We firstly fractionated Forsythiae Fructus crude extracts with organic solvents of different polarity, then the chemical profile of each fraction was analyzed by UPLC/Q‐TOF/MS, and the anticancer activity profiles of all fractions were determined by MTT assay. Next, orthogonal projections to latent structures discriminant analysis (OPLS‐DA) was applied to discriminate fractions with different anticancer activity to determine the compound(s) that contributes most to the anticancer activity. Betulinic acid was then identified to be the most potent anticancer compound in Forsythiae Fructus. Its predicted anticancer activity was confirmed by MTT assay. Taken together, our results demonstrated that the present integrated metabolomics strategy could be used for fast identification of anticancer compound(s) in herb extracts or other complex mixtures of chemicals.