Untargeted LC-MS/MS-Based Multi-Informative Molecular Networking for Targeting the Antiproliferative Ingredients in Tetradium ruticarpum Fruit

Author:

Su Chun-HanORCID,Cheng Yu-ChiehORCID,Chang Yu-ChiaORCID,Kung Ting-Hsuan,Chen Yu-LiORCID,Lai Kuei-Hung,Hsieh Hsi-LungORCID,Chen Chun-Yu,Hwang Tsong-LongORCID,Yang Yu-LiangORCID

Abstract

The fruit of Tetradium ruticarpum (TR) is commonly used in Chinese herbal medicine and it has known antiproliferative and antitumor activities, which can serve as a good source of functional ingredients. Although some antiproliferative compounds are reported to be present in TR fruit, most studies only focused on a limited range of metabolites. Therefore, in this study, the antiproliferative activity of different extracts of TR fruit was examined, and the potentially antiproliferative compounds were highlighted by applying an untargeted liquid chromatography–tandem mass spectrometry (LC-MS/MS)-based multi-informative molecular networking strategy. The results showed that among different extracts of TR fruit, the EtOAc fraction F2-3 possessed the most potent antiproliferative activity against HL-60, T24, and LX-2 human cell lines. Through computational tool-aided structure prediction and integrating various data (sample taxonomy, antiproliferative activity, and compound identity) into a molecular network, a total of 11 indole alkaloids and 47 types of quinolone alkaloids were successfully annotated and visualized into three targeted bioactive molecular families. Within these families, up to 25 types of quinolone alkaloids were found that were previously unreported in TR fruit. Four indole alkaloids and five types of quinolone alkaloids were targeted as potentially antiproliferative compounds in the EtOAc fraction F2-3, and three (evodiamine, dehydroevodiamine, and schinifoline) of these targeted alkaloids can serve as marker compounds of F2-3. Evodiamine was verified to be one of the major antiproliferative compounds, and its structural analogues discovered in the molecular network were found to be promising antitumor agents. These results exemplify the application of an LC-MS/MS-based multi-informative molecular networking strategy in the discovery and annotation of bioactive compounds from complex mixtures of potential functional food ingredients.

Funder

Chang Gung University of Science and Technology

Chang Gung Memorial Hospital

Ministry of Science and Technology, Taiwan

Publisher

MDPI AG

Subject

Chemistry (miscellaneous),Analytical Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Molecular Medicine,Drug Discovery,Pharmaceutical Science

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