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基于网络药理学和化学计量学方法的地骨皮质量标志物预测

Prediction of Lycii Cortex Quality Marker Based on Network Pharmacology and Chemometrics Methods.

作者信息

Wang Xinrui, Li Guotong, Ding Haoqiang, Du Xiqin, Zhang Lanying, Zhang Jingze, Liu Dailin

机构信息

State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.

TCM Formula R&D Department, Tianjin Modern Innovation Chinese Medicine Technology Co., Ltd., Tianjin 300380, China.

出版信息

Int J Anal Chem. 2024 Oct 22;2024:1790697. doi: 10.1155/2024/1790697. eCollection 2024.

DOI:10.1155/2024/1790697
PMID:39473702
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11521578/
Abstract

Based on the effectiveness, measurability, and traceability of the quality marker (Q-marker) theory of traditional Chinese medicine, the Q-marker of Lycii Cortex (LC) was preliminarily predicted and analyzed. A UPLC-Q-TOF-MS qualitative analysis method for LC samples was established. A total of 44 LC chemical components, 16 plasma prototype components, 25 urine prototype components, and 27 fecal prototype components were identified. At the same time, the "component-target-disease" network diagram was constructed by network pharmacology to predict the potential active components of LC. A UPLC-MS/MS quantitative analysis method was established to determine the contents of 11 components such as kukoamine A in 35 batches of LC from seven producing areas. Principal component analysis, orthogonal partial least squares discriminant analysis, and other mathematical analysis methods were used to screen the differential components. Based on the comprehensive consideration of the Q-marker traceability, transitivity, specificity, effectiveness, and measurability, kukoamine A and kukoamine B were preliminarily predicted as LC potential Q-markers, and the high-quality producing area was determined to be Chengcheng County, Weinan City, Shaanxi Province. The prediction analysis of the LC Q-marker provides a reference for the comprehensive control of the quality of LC medicinal materials and also lays a foundation for the research and exploration of the substance basis and mechanism of action of LC.

摘要

基于中药质量标志物(Q-标志物)理论的有效性、可测性和可溯源性,对地骨皮的Q-标志物进行了初步预测与分析。建立了地骨皮样品的超高效液相色谱-四极杆飞行时间质谱定性分析方法,共鉴定出44种地骨皮化学成分、16种血浆原型成分、25种尿液原型成分和27种粪便原型成分。同时,通过网络药理学构建“成分-靶点-疾病”网络图,预测地骨皮潜在活性成分。建立超高效液相色谱-串联质谱定量分析方法,测定来自7个产地的35批地骨皮中苦可胺A等11种成分的含量。采用主成分分析、正交偏最小二乘法判别分析等数学分析方法筛选差异成分。综合考虑Q-标志物的可溯源性、传递性、特异性、有效性和可测性,初步预测苦可胺A和苦可胺B为地骨皮潜在Q-标志物,并确定优质产地为陕西省渭南市澄城县。地骨皮Q-标志物的预测分析为地骨皮药材质量的全面控制提供了参考,也为地骨皮物质基础及作用机制的研究探索奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef32/11521578/71783bfeb9ef/IJAC2024-1790697.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef32/11521578/38a301777ced/IJAC2024-1790697.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef32/11521578/38a301777ced/IJAC2024-1790697.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef32/11521578/d4cfe8385d6b/IJAC2024-1790697.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef32/11521578/e6b413fa7b04/IJAC2024-1790697.003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef32/11521578/71783bfeb9ef/IJAC2024-1790697.007.jpg

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