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Identification and Quantitative Analysis of the Pharmacologically Active Components of Jianxin Granules by UHPLC-QTOF-MS/MS-Based Metabolomics

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Jianxin Granules, a Traditional Chinese Medicine (TCM), consisting of eight flavors, including Huang Qi (astragalus), Hong Shen (red ginseng), Pu Huang (pollen typhae), Dan Shen (salvia miltiorrhiza), Zhu Ling (polyporus), Bai Zhu (atractylodes macrocephala), Gui Zhi (cassia twig), Ting Li Zi (semen lepidii). Jianxin granules has a multi-system, multi-target, and multi-directional comprehensive regulatory effect on inhibiting ventricular remodeling, which is an effective formulation for the prevention and treatment of heart failure, and has a good application prospect. However, many of the ingredients, including pharmacologically active ingredients, in the Jianxin granules remain unclear. Here, we attempted to develop a metabolomics method of component identification, quantitation, pattern recognition, and cross-comparison of Jianxin granules. Chemical analysis, component identification and quantification analyse of Jianxin granules were conducted with a combination of UHPLC-QTOF-MS/MS with bioinformatics. Assessment of the correlation between technical and bio-replicated pharmacological active ingredients was implemented by Principal Component Analysis (PCA), in addition to Partial Least Squares Discriminant Analysis (PLS-DA). UHPLC-QTOFMS/ MS, a metabolomics method, was developed and adapted to characterize Jianxin granules, which consisted of 178 to 216 molecular signatures. The quantitative analysis of 95 frequently occurring molecular signatures of Jianxin granules was carried out by a single exogenous reference internal standard. Of these, 47 have been identified using diverse databases, including 2 glycosylglycerol derivatives, 2 lipids, 2 spiro compounds, 2 cyclohexanecarboxylic acids, 2 glycosides, 5 terpenoids, 7 oligopeptides, 17 favonoids, and 8 various compounds, such as hydroxycoumarin, chalcone, benzofuran, benzodioxole, benzaldehyde, aromatic ketone, and alkyl cafeate ester. The established method demonstrates robust reliability and reproducibility, making it suitable for various applications including compositional identification, quantification, and quality assessment of the pharmacologically active constituents in Jianxin granules.
Title: Identification and Quantitative Analysis of the Pharmacologically Active Components of Jianxin Granules by UHPLC-QTOF-MS/MS-Based Metabolomics
Description:
Jianxin Granules, a Traditional Chinese Medicine (TCM), consisting of eight flavors, including Huang Qi (astragalus), Hong Shen (red ginseng), Pu Huang (pollen typhae), Dan Shen (salvia miltiorrhiza), Zhu Ling (polyporus), Bai Zhu (atractylodes macrocephala), Gui Zhi (cassia twig), Ting Li Zi (semen lepidii).
Jianxin granules has a multi-system, multi-target, and multi-directional comprehensive regulatory effect on inhibiting ventricular remodeling, which is an effective formulation for the prevention and treatment of heart failure, and has a good application prospect.
However, many of the ingredients, including pharmacologically active ingredients, in the Jianxin granules remain unclear.
Here, we attempted to develop a metabolomics method of component identification, quantitation, pattern recognition, and cross-comparison of Jianxin granules.
Chemical analysis, component identification and quantification analyse of Jianxin granules were conducted with a combination of UHPLC-QTOF-MS/MS with bioinformatics.
Assessment of the correlation between technical and bio-replicated pharmacological active ingredients was implemented by Principal Component Analysis (PCA), in addition to Partial Least Squares Discriminant Analysis (PLS-DA).
UHPLC-QTOFMS/ MS, a metabolomics method, was developed and adapted to characterize Jianxin granules, which consisted of 178 to 216 molecular signatures.
The quantitative analysis of 95 frequently occurring molecular signatures of Jianxin granules was carried out by a single exogenous reference internal standard.
Of these, 47 have been identified using diverse databases, including 2 glycosylglycerol derivatives, 2 lipids, 2 spiro compounds, 2 cyclohexanecarboxylic acids, 2 glycosides, 5 terpenoids, 7 oligopeptides, 17 favonoids, and 8 various compounds, such as hydroxycoumarin, chalcone, benzofuran, benzodioxole, benzaldehyde, aromatic ketone, and alkyl cafeate ester.
The established method demonstrates robust reliability and reproducibility, making it suitable for various applications including compositional identification, quantification, and quality assessment of the pharmacologically active constituents in Jianxin granules.

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