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基于UHPLC-Q-TOF-MS联用多平台数据整合技术对当归-苦参药对血浆和尿液中化学成分及代谢产物的全面分析

Comprehensive Profiling of Chemical Constituents and Metabolites of the Angelica sinensis-Sophora flavescens Herbal Pair in Plasma and Urine via UHPLC-Q-TOF-MS Coupled With Multi-Platform Data Integration.

作者信息

Bai Lincheng, Chen Pengyi, Xu Jiaqi, Yi Zeyu, Wang Tiantian, Han Hua, Dong Peiliang

机构信息

Heilongjiang University of Chinese Medicine, College of Medicine, Harbin, China.

Institute of Traditional Chinese Medicine, Heilongjiang University of Chinese Medicine, Harbin, China.

出版信息

J Sep Sci. 2025 Jun;48(6):e70201. doi: 10.1002/jssc.70201.

Abstract

The traditional Chinese Danggui-Kushen herbal pair (DKHP) has garnered widespread attention in the treatment of myocardial ischemia. However, the intricate nature of traditional Chinese medicine components and the ambiguity in their constituent analyses have considerably impeded further clinical advancements. Therefore, it is crucial to clarify the principal constituents of DKHP and its metabolic byproducts in the body. In this study, various mass spectrometry (MS) optimization software were used to analyze the chemical characteristics of Angelica sinensis-Sophora sophora (DKHP) and identify the chemical constituents entering rat serum and urine after oral gavage administration in rats. A total of 10 male Sprague-Dawley rats were used in this study. Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight MS was performed. Based on this, we developed a method to identify chemical constituents using UNIFI for the acquired MS data. Subsequently, MS-DIAL was utilized to process the complex MS data, including peak detection, fitting, and alignment. A feature-based molecular networking was constructed on the Global Natural Product Social molecular networking platform, establishing correlations for individual nodes, including common neutral losses and product ions, which serve as important tools for inferring unknown compounds. A multi-stage intelligent data annotation strategy was developed. In addition, molecular simulations were performed using density functional theory to determine the plausibility of the compound cleavage reactions and further confirm the compound structures. Finally, molecular docking technology was employed to evaluate the binding affinity and identify potential active metabolites. DKHP analysis resulted in the identification or preliminary characterization of 109 chemical constituents, primarily flavonoids, alkaloids, and phenolic acid compounds. In addition, 11 prototype products and 99 metabolites were detected in rat serum and urine.

摘要

传统中药当归-苦参药对(DKHP)在心肌缺血治疗中受到广泛关注。然而,中药成分的复杂性及其成分分析的模糊性极大地阻碍了进一步的临床进展。因此,明确DKHP的主要成分及其体内代谢产物至关重要。本研究采用多种质谱(MS)优化软件分析当归-苦参(DKHP)的化学特性,并鉴定大鼠灌胃给药后进入大鼠血清和尿液的化学成分。本研究共使用了10只雄性Sprague-Dawley大鼠。采用超高效液相色谱-四极杆飞行时间质谱联用技术。在此基础上,我们开发了一种利用UNIFI对采集的MS数据进行化学成分鉴定的方法。随后,利用MS-DIAL处理复杂的MS数据,包括峰检测、拟合和比对。在全球天然产物社会分子网络平台上构建了基于特征的分子网络,为各个节点建立了相关性,包括常见的中性损失和产物离子,这些是推断未知化合物的重要工具。制定了多阶段智能数据注释策略。此外,利用密度泛函理论进行分子模拟,以确定化合物裂解反应的合理性,并进一步确认化合物结构。最后,采用分子对接技术评估结合亲和力并鉴定潜在的活性代谢产物。对DKHP的分析鉴定或初步表征了109种化学成分,主要为黄酮类、生物碱类和酚酸类化合物。此外,在大鼠血清和尿液中检测到11种原型产物和99种代谢产物。

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