Xiao Jianzhong Granules (XJZG), a well-known traditional prescription with protective effects on the gastric mucosa, as documented in the Treatise on Typhoid and Miscellaneous Diseases. Clinical studies have proven that XJZG exhibits significant anti-colitis properties and effectively alleviates duodenal ulcers. However, despite its clinical popularity, comprehensive studies on its chemical composition and in vivo metabolism remain limited. In the present study, gas chromatography coupled with mass spectrometry (GC-MS) and ultra-high-performance liquid chromatography coupled with Q-Exactive Orbitrap mass spectrometry (UHPLC Q-Exactive Orbitrap MS) were used to analyze the chemical composition of XJZG, while it is in vivo metabolic profile was further assessed with UHPLC Q-Exactive Orbitrap MS. Additionally, ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-MS/MS) was utilized to quantify its primary components. As a result, a total of 51 volatiles were characterized by GC-MS, and 139 compounds were characterized by UHPLC Q-Exactive Orbitrap MS in vitro. In addition, 51 prototype components and 133 metabolites were characterized in vivo. Notably, 5 new compounds were discovered in this process. The main metabolic reactions included oxidation, reduction, hydrolysis, glucuronidation, and sulfate esterification. In quantitative analysis, 17 components were determined and successfully applied for detection by UPLC-MS/MS in multiple reaction monitoring mode. The quantitative methods were validated and met the requirements. Through multivariate statistical analysis, 6 components were selected as potential quality markers for XJZG based on PCA and OPLS-DA. Additionally, our study provides supplementary chemical evidence to further elucidate the material basis of XJZG.

2025-08-01·Talanta

Intelligent characterization multi-components in Yangxinshi tablet by online comprehensive two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry combined with deep learning-assisted mass defect filtering classification and multidimensional data annotation strategy

Article

作者: Du, Kunze ; Li, Jin ; Chen, Shujing ; Chang, Yanxu ; Zhang, Lili ; Wei, Wei ; Wen, Jiake ; Wang, Xiaoyan ; Xu, Jixiang

A comprehensive characterization strategy for the intelligent analysis of multiple chemical components in Yangxinshi Tablet (YXST) was established. The strategy developed the deep learning-assisted mass defect filtering intelligent classification, preferred ions capture list and active exclusion (DLA-MDF-PIL-AE) data acquisition mode by online comprehensive two-dimensional liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (2DLC-Q-TOF-MS/MS). Firstly, the online 2DLC-Q-TOF-MS/MS system was constructed and the orthogonality was evaluated. Secondly, the user interface for deep learning-assisted MDF intelligent classification technology was developed and applied to compounds classification to generate preferred ion capture lists of various types compounds. Finally, molecular networking (MN), associated neutral loss (NL) fragments, and characteristic diagnosis ion (CDI) were utilized for the automatic and manual annotation of compounds, respectively. As a result, a total of 228 compounds including 80 flavanoids, 52 alkaloids, 36 phenolic acids, 15 terpenoids, 17 saponins and 28 others were preliminary identified from YXST and source attribution was assigned to them. Furthermore, 39 compounds were simultaneously quantified by ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-MS/MS) method. Conclusively, the proposed integrated strategy proved to be a powerful method for characterizing multiple components in complex natural products.

2025-06-01·Biotechnology Letters

Network pharmacology, molecular docking, molecular dynamics simulation, and experiment verification analysis to reveal the action mechanism of RenShen Guipi Wan in the treatment of anemia

Article

作者: Yun, Keming ; Zhang, Nan ; An, Quan ; Liu, Xuyuan ; Li, Chen ; Qu, Tingli

OBJECTIVETo explore the action mechanisms of RGW that may treat anemia through the integration of network pharmacology, molecular docking, molecular dynamics simulation, and experiment verification.RESULTIn particular, Ginsenoside Rg4, Ginsenoside Rg1, 3,3',4,4'-Tetrahydroxy 2-methoxychalcone, Ginsenoside F1, Glycyrol, Chalconaringenin 4'-glucoside, Licochalcone B, 4',7-Dihydroxyflavone, Glycycoumarin, and Ginsenoside Rh1 were the core components, while TP53, STAT3, PIK3R1, SRC, HIF-1α were the core targets. The GO and KEGG analyses indicated that RGW may modulate multiple biological processes and pathways, including the PI3K-Akt, HIF-1, and NF-kappa B signaling pathways, as well as EGFR tyrosine kinase inhibitor resistance. Molecular docking and molecular dynamics simulations showed good affinity between the active components and core targets of RGW, with stable binding within 100 nano seconds. Experiment verification revealed RGW could improve the routine blood markers of mice, and decrease the level of HIF-1α significantly.CONCLUSIONRGW may treat anemia by regulating the PI3K-Akt and HIF-1 signaling pathways. It demonstrates the potential pharmacological mechanism of RGW in the treatment of anemia and provides a reference for clinical application of this formula.

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适应症	最高研发状态	国家/地区	公司	日期
急性肺损伤	临床前	韩国	Yeungnam University	2024-07-03
乳腺癌	临床前	韩国	Yeungnam University	2024-07-03
心脏损伤	临床前	韩国	Yeungnam University	2024-07-03
肝细胞癌	临床前	韩国	Yeungnam University	2024-07-03
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炎症	临床前	韩国	Yeungnam University	2024-07-03
骨肉瘤	临床前	韩国	Yeungnam University	2024-07-03
口腔鳞状细胞癌	临床前	韩国	Yeungnam University	2024-07-03
自身免疫性疾病	临床前	中国	湖北科技学院	2024-02-01
自身免疫性疾病	临床前	中国	中国人民解放军总医院	2024-02-01