Q-Marker Prediction of Astragali Complanati Semen Based on Fingerprint and Network Pharmacology

杨梅素 高效液相色谱法 根(腹足类) 指纹(计算) 化学 中医药 色谱法 传统医学 药理学 医学 生物 人工智能 计算机科学 生物化学 槲皮素 山奈酚 病理 替代医学 植物 抗氧化剂
作者
Xiaozhou Jia,Weisheng Lv,Cuijie Wei,Yueyi Liang,Jie Yang,Xuemei Hou,Zhenyu Li,Xiangdong Chen,Mei Wei,Dongmei Sun
出处
期刊:Journal of AOAC International [Oxford University Press]
卷期号:108 (1): 78-89 被引量:1
标识
DOI:10.1093/jaoacint/qsae077
摘要

Abstract Background Astragali Complanati, known in Chinese as Shayuanzi, is a common medicinal material in traditional Chinese medicine, mainly used for tonifying the kidney, supporting yang, consolidating essence, reducing urine, and other diseases. Objective The ultra performance liquid chromatography (UPLC) fingerprint of Astragali Complanati Semen (ACS) was established, and the Q-markers of ACS were analyzed by network pharmacology. Methods First, a UPLC fingerprint detection method was established for ACS, and the common peaks were identified by UPLC–MS/MS. The “component–target–pathway” network relationships of characteristic components of ACS were constructed by network pharmacology, and the potential quality markers (Q-markers) were predicted. Results A total of 24 common peaks were identified from the UPLC fingerprint of ACS, and 12 chromatographic peaks were identified by UPLC–MS/MS. A total of 12 Q-markers candidate components were screened out. Through network pharmacological analysis, it is predicted that myricetin 3-O-β-D-xylopyranosyl-(1–2)-[α-L-rhamnopyranosyl-(1–6)]-β-D-glucopyranoside, myricetin 3-O-β-D-xylopyranosyl(1–2)-β-D-glucopyranoside, myricetin 3-β-D-glucopyranoside, cannabiscitrin, laricitrin-3-O-glucoside, leucoside, complanatoside B, complanatuside, complanatuside 6''-malonate, clycosin, rhamnocitrin 3-O-β-D-apiofuranosyl(1→2)-β-D-glucopyranoside, and 3-O-[5'''-O-feruloyl-beta-D-apiofuranosyl(1'''->2'')-beta-D-glucopyranosyl] rhamnocitrin are the Q-markers of ACS. Conclusion The method established in this study was accurate, reliable, simple, and practical and could be used as a reference method for ACS quality detection. Twelve Q-markers selected by network pharmacology could provide support and references for ACS QC.
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