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基于超高效液相色谱-四极杆飞行时间质谱的网络药理学整合代谢组学策略解析款冬花生品与炮制品的差异有效成分。

A network pharmacology-integrated metabolomics strategy for clarifying the difference between effective compounds of raw and processed Farfarae flos by ultra high-performance liquid chromatography-quadrupole-time of flight mass spectrometry.

机构信息

Tianjin State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 300193, China; Tianjin Key Laboratory of Phytochemistry and Pharmaceutical Analysis, Tianjin University of Traditional Chinese Medicine, Tianjin, 300193, China.

Tianjin State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 300193, China; Tianjin Key Laboratory of Phytochemistry and Pharmaceutical Analysis, Tianjin University of Traditional Chinese Medicine, Tianjin, 300193, China.

出版信息

J Pharm Biomed Anal. 2018 Jul 15;156:349-357. doi: 10.1016/j.jpba.2018.05.003. Epub 2018 May 4.

DOI:10.1016/j.jpba.2018.05.003
PMID:29753281
Abstract

This study aimed to clarify the difference between the effective compounds of raw and processed Farfarae flos using a network pharmacology-integrated metabolomics strategy. First, metabolomics data were obtained by ultra high-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF/MS). Then, metabolomics analysis was developed to screen for the influential compounds that were different between raw and processed Farfarae flos. Finally, a network pharmacology approach was applied to verify the activity of the screened compounds. As a result, 4 compounds (chlorogenic acid, caffeic acid, rutin and isoquercitrin) were successfully screened, identified, quantified and verified as the most influential effective compounds. They may synergistically inhibit the p38, JNK and ERK-mediated pathways, which would induce the inhibition of the expression of the IFA virus. The results revealed that the proposed network pharmacology-integrated metabolomics strategy was a powerful tool for discovering the effective compounds that were responsible for the difference between raw and processed Chinese herbs.

摘要

本研究旨在采用网络药理学整合代谢组学策略,阐明生、炒款冬花的有效化合物之间的差异。首先,通过超高效液相色谱-四极杆飞行时间质谱联用技术(UHPLC-Q-TOF/MS)获得代谢组学数据。然后,进行代谢组学分析以筛选生、炒款冬花之间有差异的影响性化合物。最后,应用网络药理学方法验证筛选出的化合物的活性。结果成功筛选、鉴定、定量和验证了 4 种化合物(绿原酸、咖啡酸、芦丁和异槲皮苷),它们可能协同抑制 p38、JNK 和 ERK 介导的途径,从而诱导抑制 IFA 病毒的表达。结果表明,所提出的网络药理学整合代谢组学策略是发现生、炒中药差异的有效化合物的有力工具。

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