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Combination of high‐resolution accurate mass spectrometry and network pharmacology provides a new method for the chemical constituents' study and target prediction in vivo of Garcinia multiflora.

Authors :
Li, Zhuolun
Zuo, Lihua
Shi, Yingying
Tian, Dongsong
Liu, Liwei
Yang, Yantao
Zhou, Lin
Zhang, Xiaojian
Kang, Jian
Hao, Xiaojiang
Yuan, Chunmao
Sun, Zhi
Source :
Journal of Separation Science. Mar2020, Vol. 43 Issue 5, p978-986. 9p.
Publication Year :
2020

Abstract

Garcinia multiflora is a kind of evergreen tree which is widely distributed in the south of China. However, few researches focused on the constituents in different parts of G. multiflora as well as their potential targets and pathways in vivo. To clarify the chemical constituents of G. multiflora rapidly and predict the potential targets as well as pathways in vivo that this plant may have effects on, a feasible and accurate strategy was developed to identify the chemical constituents in fruits, leaves, and branches of G. multiflora by ultra‐high performance liquid chromatography with Q‐Exactive hybrid quadrupole‐orbitrap high‐resolution accurate mass spectrometry. Network pharmacology was then employed and a "compounds‐targets‐diseases" network was established. Sixty‐one compounds including polycyclic polyprenylated acylphloroglucinols, xanthones, and flavonoids were finally identified in different parts of G. multiflora, and the contents of seven constituents were quantified, respectively. On the basis of the network pharmacology analysis results, compounds in this plant were speculated to have potential pharmacodynamic effect on cancer, inflammatory, respiratory diseases, cardiovascular diseases, and metabolic diseases. This research will provide a new method for the advanced study on the pharmacodynamic materials basis of G. multiflora, and offer valuable evidences for medicinal purpose of this plant. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16159306
Volume :
43
Issue :
5
Database :
Academic Search Index
Journal :
Journal of Separation Science
Publication Type :
Academic Journal
Accession number :
142139075
Full Text :
https://doi.org/10.1002/jssc.201900755