基于网络药理学和UPLC指纹图谱的紫苏质量标志物(Q-Marker)预测  

Prediction of Q-Marker in Perilla frutescens(L.)Britt based on UPLC fingerprint and network pharmacology

作　　者：张良琦 陈凡 张子桉 林云 周春娇 汤卓翰 江星明[1] 肖美凤[1,2,3] ZHANG Liang-qi;CHEN Fan;ZHANG Zi-an;LIN Yun;ZHOU Chun-jiao;TANG Zhuo-han;JIANG Xing-ming;XIAO Mei-feng(College of Pharmacy,Hunan University of Chinese Medicine;Hunan Key Laboratory of Druggability and Preparation Modification for Traditional Chinese Medicine(TCM);Property and Pharmacodaynamic Key Laboratory of TCM,National Administration of TCM,Changsha 410208,China)

机构地区：[1]湖南中医药大学药学院 [2]中药成药性与制剂制备湖南省重点实验室 [3]中药药性与药效国家中医药管理局重点实验室,长沙410208

出　　处：《天然产物研究与开发》2024年第10期1800-1812,共13页Natural Product Research and Development

基　　金：湖南省中医药科研计划(B2024010);湖南中医药大学本科生科研创新基金(2023BKS114);湖南中医药大学研究生科研创新项目(2024CX091,2024XC168)。

摘　　要：基于UPLC指纹图谱和网络药理学法分析并筛选紫苏潜在质量标志物(Q-Marker)。首先建立15批紫苏叶及14批紫苏梗的指纹图谱,并对不同来源、批次的紫苏叶和紫苏梗中的成分及含量进行比较,标定紫苏不同部位指纹图谱的共有峰和非共有峰;采用网络药理学法构建紫苏“成分-靶点”网络图,并构建靶点蛋白互作网络图,预测紫苏Q-Marker。本研究建立的紫苏不同部位的指纹图谱,共检测到了5种成分,其中迷迭香酸、咖啡酸、木犀草素-7-O-葡萄糖醛酸苷、木犀草素-7-O-二葡萄糖醛酸苷为叶和梗的共有成分,芹菜素-7-O-葡萄糖醛酸苷为紫苏叶特有成分。筛选得到包括MAPK1、PIK3CA等在内的14个核心靶点,对以上靶点进行GO和KEGG功能分析可知涉及肿瘤坏死因子、新冠肺炎、脂质和动脉粥样硬化等通路,最后构建“成分-靶点-通路”网络图,选取排名前4的靶蛋白与4个成分进行分子对接验证,结果显示成分与蛋白之间具有十分良好的结合性能。本实验基于UPLC法建立紫苏不同部位多成分含量测定方法,此方法操作简单、准确度高,可作为紫苏质量检测的参考方法;同时结合网络药理学和分子对接技术预测迷迭香酸、咖啡酸、木犀草素-7-O-葡萄糖醛酸苷、木犀草素-7-O-二葡萄糖醛酸苷为紫苏潜在质量标志物,以此来评价紫苏“多成分-多靶点-多通路”的协同作用,为紫苏的质量控制提供了理论依据,同时也为后续的紫苏药效物质基础和作用机制提供坚实的基础。This study aims to analyze and predict the potential quality markers of different parts of Perilla frutescens(L.)Britt based on UPLC fingerprint analysis method and network pharmacology.The fingerprints of 15 batches of P.frutescens leaves and 14 batches of P.frutescens stems were established,and the components and contents of P.frutescens leaves and P.frutescens stems from different places of origin and batches were compared,and the common peaks and non-common peaks of different parts of P.frutescens were calibrated.Through network pharmacology to construct the visualization of′target-protein′interaction network in P.frutescens,a′component-target′network diagram was constructed to predict Q-Marker in P.frutescens.In this study,a total of five components were detected in the fingerprints of different parts of P.frutescens,among which rosmarinic acid,caffeic acid,luteolin-7-O-glucuronide and luteolinl-7-O-diglucuronide were common components of P.frutescens leaves and P.frutescens stems,and apigenin-7-O-glucuronide were unique components of P.frutescens leaves.Fourteen core targets including MAPK1,PIK3CA were screened by network pharmacology.GO and KEGG functional analysis of these targets showed that TNF,COVID-19,lipid and atherosclerosis signaling pathway were involved,and“component-target-pathway”'network was finally constructed.The top four target proteins and four components were selected for molecular docking verification,The results showed that there was a very good binding performance between the components and the proteins.Based on UPLC fingerprint analysis and network pharmacology,rosmarinic acid,caffeic acid,luteolin-7-O-glucuronide and luteolinl-7-O-diglucuronide were predicted to be potential Q-Marker for different parts of P.frutescens.highlighting the synergistic interactions of‘multi-component multi-target multi-pathway’in P.frutescens,which provided a theoretical framework for the quality control of P.frutescens,and also provided a robust foundation for the subsequent material basi

关 键 词：紫苏 指纹图谱 质量标志物 网络药理学 化学成分 

分 类 号：R284.1[医药卫生—中药学] R285[医药卫生—中医学]