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基于核磁共振光谱法的双黄连注射液化学成分定性与定量评价

Qualitative and Quantitative Evaluation of Chemical Constituents from Shuanghuanglian Injection Using Nuclear Magnetic Resonance Spectroscopy.

作者信息

Wang Ziyan, Wang Zuoyuan, Jiang Miaomiao, Yang Jing, Meng Qingfen, Guan Jianli, Xu Maoling, Chai Xin

机构信息

State Key Laboratory of Component-based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.

Henan Fusen Pharmaceutical Co.,Ltd., Henan 474450, China.

出版信息

J Anal Methods Chem. 2022 Mar 9;2022:7763207. doi: 10.1155/2022/7763207. eCollection 2022.

DOI:10.1155/2022/7763207
PMID:35309716
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8926469/
Abstract

By employing nuclear magnetic resonance (NMR), we implemented a chemical research on Shuanghuanglian injection (SHLI) and identified 17 components, including eight primary metabolites and nine secondary metabolites. Guided by the approach of network pharmacology, the potential activities were briefly predicted for seven primary metabolites except for formic acid, such as anti-inflammation, antioxidation, and cardiovascular protection. The focused primary metabolites were quantified by a proton nuclear magnetic resonance (H-NMR) method, which was verified with good linearity and satisfactory precision, repeatability, stability, and accuracy (except for -inositol with mean recovery at 135.78%). Based on the successfully established method, seven primary metabolites were effectively quantified with a slight fluctuation in 20 batches of SHLIs. The average total content of these compounds was 6.85 mg/mL, accounting for 24.84% in total solid of SHLI. This research provides an alternative method for analysis of primary metabolites and contributes to the quality control of SHLI.

摘要

通过采用核磁共振(NMR)技术,我们对双黄连注射液(SHLI)进行了化学研究,鉴定出17种成分,包括8种初级代谢产物和9种次级代谢产物。在网络药理学方法的指导下,除甲酸外,对7种初级代谢产物的潜在活性进行了简要预测,如抗炎、抗氧化和心血管保护。通过质子核磁共振(H-NMR)方法对重点初级代谢产物进行定量,该方法具有良好的线性关系,精密度、重复性、稳定性和准确性均令人满意(除肌醇的平均回收率为135.78%外)。基于成功建立的方法,对20批双黄连注射液中的7种初级代谢产物进行了有效定量,含量略有波动。这些化合物的平均总含量为6.85mg/mL,占双黄连注射液总固体的24.84%。本研究为初级代谢产物的分析提供了一种替代方法,有助于双黄连注射液的质量控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/32811d44d02a/JAMC2022-7763207.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/e82be9f5096f/JAMC2022-7763207.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/d588a430a965/JAMC2022-7763207.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/c3072e0a884c/JAMC2022-7763207.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/997085fe123d/JAMC2022-7763207.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/32811d44d02a/JAMC2022-7763207.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/e82be9f5096f/JAMC2022-7763207.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/d588a430a965/JAMC2022-7763207.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/c3072e0a884c/JAMC2022-7763207.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/997085fe123d/JAMC2022-7763207.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/855c/8926469/32811d44d02a/JAMC2022-7763207.005.jpg

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2
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Nucleic Acids Res. 2019 Jul 2;47(W1):W357-W364. doi: 10.1093/nar/gkz382.
3
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4
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Phytochem Anal. 2019 Nov;30(6):617-622. doi: 10.1002/pca.2834. Epub 2019 Apr 24.
5
PubChem 2019 update: improved access to chemical data.PubChem 2019 年更新:改善化学数据获取。
Nucleic Acids Res. 2019 Jan 8;47(D1):D1102-D1109. doi: 10.1093/nar/gky1033.
6
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Microb Pathog. 2018 Aug;121:318-324. doi: 10.1016/j.micpath.2018.06.004. Epub 2018 Jun 2.
7
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J Nat Med. 2018 Jun;72(3):793-797. doi: 10.1007/s11418-018-1203-0. Epub 2018 Mar 22.
8
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9
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Oncotarget. 2017 Dec 22;9(6):6771-6779. doi: 10.18632/oncotarget.23645. eCollection 2018 Jan 23.
10
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J Cancer. 2017 Jul 3;8(10):1872-1883. doi: 10.7150/jca.15407. eCollection 2017.