基于植物代谢组学和网络药理学分析预测鸡骨草药材的质量标志物  

Predictive Analysis of Quality Markers of Abrus cantoniensis Hance Based on Plant Metabolomics and Network Pharmacology

作　　者：徐月阳 史军杰 彭丽华 方碧烟 陈炜璇 成金乐 Xu Yueyang;Shi Junjie;Peng Lihua;Fang Biyan;Chen Weixuan;Cheng Jinle(School of Chinese Materia Medica,Guangzhou University of Chinese Medicine,Guangzhou 510006,China;Key Laboratory of Chinese Medicinal Resource from Lingnan,Ministry of Education,Research Center of Chinese Herbal Resource Science and Engineering,Guangzhou University of Chinese Medicine,Guangzhou 510006,China;South China Laboratory for Pharmaceutical Research and Development,National Engineering and Technology Research Center for Chinese Patent Medicine,Guangzhou 510006,China;Zhongshan Zhongzhi Pharmaceutical Group Co.Ltd,Zhongshan 528437,China)

机构地区：[1]广州中医药大学中药学院,广州510006 [2]广州中医药大学中药资源科学与工程研究中心/岭南中药资源教育部重点实验室,广州510006 [3]国家中成药工程技术研究中心、南药研发实验室,广州510006 [4]中山市中智药业集团有限公司,中山528437

出　　处：《世界科学技术-中医药现代化》2023年第6期1972-1986,共15页Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology

基　　金：广东省科学技术厅广东省重点领域研发计划项目(2020B1111110007):20种岭南中药材质量标准国际化示范研究,负责人:果德安;中山市中智药业集团有限公司:岭南中药材鸡骨草质量标准国际化示范研究,负责人:成金乐。

摘　　要：目的基于植物代谢组学分析鸡骨草药材的次生代谢产物,并结合多元统计学和网络药理学预测分析鸡骨草药材的质量标志物(Q-Marker)。方法建立UPLC-Q-TOF-MS分析方法,分析11批次鸡骨草药材的化学成分,确定其共有成分。通过聚类分析(HCA)、主成分分析(PCA)和偏最小二乘判别分析(OPLS-DA)确认造成11批次鸡骨草药材分类的主要差异成分,再运用网络药理学构建“核心成分-核心靶点-核心通路”网络,筛选预测鸡骨草药材的潜在Q-Marker,并进行分子对接验证其活性。结果11批次鸡骨草药材中含有39个共有成分,主要为三萜皂苷类、黄酮类、生物碱类等。经聚类分析和主成分分析显示11批次鸡骨草药材分为4类,后经偏最小二乘判别分析发现其中9个化学成分在分类中起重要作用。网络药理学分析结果表明,以上9个成分为活性成分,作用于166个靶点,通过蛋白质互作(PPI)筛选得到29个核心靶点,其中4个化学成分相思子碱、下箴刺桐碱、大豆皂苷Ⅰ、精氨酸与核心靶点的关联度高,结合QMarker理念及分子对接结果,初步预测相思子碱和下箴刺桐碱为鸡骨草药材的Q-Marker。结论利用植物代谢组学结合多元统计学和网络药理学预测分析鸡骨草药材的Q-Marker,为鸡骨草药材的质量控制与评价提供数据参考,为进一步科学开发鸡骨草药材提供研究思路。Objective To analyze the secondary metabolites of Abrus cantoniensis Hance based on plant metabolomics,and the quality marker(Q-marker)of Abrus cantoniensis Hance by multivariate statistics and network pharmacology prediction.Methods The chemical constituents of 11 batches of Abrus cantoniensis Hance were analyzed by UPLC-Q-TOF-MS methods established and their common components were confirmed.At the same time,cluster analysis(HCA),principal component analysis(PCA)and partial least squares discriminant analysis(OPLS-DA)were carried out to identify the main differential components that caused the classification of the multi-batch medicinal materials of Abrus cantoniensis Hance.Then,the network of"core components-core target-core pathway"was constructed through network pharmacology to screen and predict the potential Q-marker of Abrus cantoniensis Hance,and molecular docking verification was applied to further predict the activity.Results 39 common components were identified in 11 batches of Abrus cantoniensis Hance,mainly containing triterpenoid saponins,flavonoids,alkaloids,etc.HCA and PCA analysis showed that 11 batches of Abrus cantoniensis Hance were divided into 4 categories,and OPLS-DA analysis showed that 9 chemical components played an important role in the classification.The results of network pharmacology analysis showed that the above 9 components which acted on 166 targets were active components,and 29 core targets were obtained by protein interaction(PPI)screening.Among them,four chemical components,Abrine,Hypaphorine,SoyasaponinⅠand Arginine,were highly correlated with the core targets.Combined with the concept of Q-marker and molecular docking results,it was preliminarily predicted that Abrine and Hypaphorine would be the Q-markers of Abrus cantoniensis Hance.Conclusion The Q-marker of Abrus cantoniensis Hance can be predicted and analyzed by plant metabolomics combined with multivariate statistics and network pharmacology.This study provided data reference for the quality control and evaluation of

关 键 词：鸡骨草药材 质量标志物 植物代谢组学 网络药理学 相思子碱 下箴刺桐碱 

分 类 号：R284.1[医药卫生—中药学]