MS/MS similarity networking accelerated target profiling of triterpene saponins in Eleutherococcus senticosus leaves.

The targeted mass information of compounds accelerated their discovery in a large volume of untargeted MS data. An MS/MS similarity networking is advanced in clustering the structural analogues, which benefits the collection of mass information of similar compounds. The triterpene saponins extracted from Eleutherococcus senticosus leaves (ESL), a kind of functional tea, have shown promise in the relief of Alzheimer's disease. In this work, a target-precursor list (TPL) generated using MS/MS similarity networking was employed to rapidly trace 106 triterpene saponins from the aqueous extracts of ESL, of which 49 were tentatively identified as potentially new triterpene saponins. Moreover, a compound database of triterpene saponins was established and successfully applied to uncover their distribution features in ESL samples collected from different areas.