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Updated: Dec 8, 2025

Mass Spectrometry-Guided Genome Mining as a Tool to Uncover Novel Natural Products
Published on: March 12, 2020
ComMSnDB-An Automatable Strategy to Identify Compounds from MS Data Sets (Identification of Gypenosides as an
Xin Wang1,2, Dan Li3, Xiaomin Guo1
1School of Pharmacy, Fudan University, Shanghai 200135, P. R. China.
Abstract:
Gynostemma pentaphyllum (Thunb.) Makino is a popular functional food and is also used as an important medicinal plant in China. Gypenoside, the main active constituent in G. pentaphyllum (Thunb.) Makino, belongs to dammarane-type triterpenoid saponins. Due to its high molecular weight and high polarity, it is difficult to obtain complete compound information for gypenoside extracts via mass spectrometry experiments. In this study, an automated targeted data postprocessing strategy called Compound MSn Database (ComMSnDB) was designed and established to elucidate compounds in gypenoside extracts based on ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry (UHPLC-ESI-Q-TOF-MS/MS). As a result, 18 types of and 199 main saponin constituents, including 47 potential novel compounds, were tentatively identified from different habitats. At the same time, 15 gypenoside standard compounds were used to verify the feasibility of the ComMSnDB strategy. These results demonstrated that ComMSnDB offers practical value for quick, automated, and effective compound identification.

