An efficient and green separation method of total alkaloids by resorcinol-formaldehyde aerogel during extraction of Coptis chinensis

Zhu, Yong; Li, Hailun; Jin, Huiran; Ma, Jingrui; Ye, Zhandong; Wu, Bingmin; Zhang, Ying; Xiong, Qingping; Ding, Shangwu; Chen, Jing; Huang, Song

doi:10.1016/j.indcrop.2023.116438

Cited by 2 publications

(2 citation statements)

References 54 publications

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“…The establishment of multi-component detection and a fingerprinting method based on selected quality markers could provide comprehensive quality control of complex systems. 10,11 Alkaloids are widely present in natural products, such as Ephedrae herba, 12,13 Coptis chinensis Franch., 14,15 Aconitum carmichaeli Debx., 16 and Datura metel L., 17,18 which are very suitable as markers for controlling product quality. Similarly, alkaloids are the main active ingredients in SC.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive strategy for quality marker discovery using chemical profiling combined with chemometrics, machine learning and network pharmacology analysis: taking Sinomenii Caulis as an example

Zhang,

Ren,

et al. 2023

New J. Chem.

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Section: Introductionmentioning

confidence: 99%

A comprehensive strategy for quality marker discovery using chemical profiling combined with chemometrics, machine learning and network pharmacology analysis: taking Sinomenii Caulis as an example

Zhang,

Ren,

et al. 2023

New J. Chem.

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“…Alkaloids are widely present in natural products, such as Ephedrae herba 12,13 ,Coptis chinensis Franch. 14,15 ,Aconitum carmichaeli Debx. 16 , Datura metel L. 17,18 , which is very suitable as a marker for controlling product quality.…”

Section: Introductionmentioning

confidence: 99%

Integration of UPLC-Q-TOF-MS/MS, chemometrics and network pharmacology to discovery potential quality markers in Sinomenii Caulis

Zhang

Ren

et al. 2023

Preprint

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Rationale: There are significant differences in Sinomenii Caulis (SC) obtained from different geographical regions and medicinal plant parts. This study aims to explore potential quality markers that are correlated with clinical efficacy in SC by a comprehensive strategy that integrates chemical profiling, chemometrics, and network pharmacology. Methods: First, an alkaloid database was created through the utilization of the UNIFI system to qualitatively analyze of alkaloids in SC. Then, differential compounds in SC collected from various geographic regions were screened by applying multivariate data analysis. Subsequently, the support vector machine (SVM) and random forest (RF) algorithms are adopted to calculate the grouping accuracy of different components. Finally, network pharmacology was conducted to analyze the pharmacological properties and potential associations of these target compounds. Results: A total of 81 alkaloids were identified from SC samples, including 13 aporphine alkaloids, 18 protoberberine alkaloids, 32 morphine alkaloids, 10 benzylisoquinoline alkaloids, and 8 other types of alkaloids. Notably, palmatine, sinoracutine, and magnoflorine are active ingredients with the ability to differentiate the different regions of SC samples. And thus should be prioritized when selecting quality markers. Additionally, it was observed that the RF algorithms demonstrated higher classification accuracy than the SVM model. Conclusion: This comprehensive strategy may prove to be a powerful technique for screening the quality markers components, which could be used for the quality control of SC, and can serve as reference for design of quality control of other herbs.

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An efficient and green separation method of total alkaloids by resorcinol-formaldehyde aerogel during extraction of Coptis chinensis

Cited by 2 publications

References 54 publications

A comprehensive strategy for quality marker discovery using chemical profiling combined with chemometrics, machine learning and network pharmacology analysis: taking Sinomenii Caulis as an example

A comprehensive strategy for quality marker discovery using chemical profiling combined with chemometrics, machine learning and network pharmacology analysis: taking Sinomenii Caulis as an example

Integration of UPLC-Q-TOF-MS/MS, chemometrics and network pharmacology to discovery potential quality markers in Sinomenii Caulis

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