A Comprehensive Analysis of Volatile and Nonvolatile Components in Berberis fortunei and Its Inhibition Against HT29 Colorectal Cancer Cells Through GC-IMS, LC-QTOF-MS, and Docking-Based Network Analysis.

IF 2.6 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Phytochemical Analysis Pub Date : 2025-12-01 Epub Date: 2025-03-04 DOI:10.1002/pca.3523
Fang-Tong Liu, Yue-Hua Chen, Wen-Yu Wang, Jia-Nuo Zhang, Rui-Bo Sun, Xin-Ru Zhang, Yu-Tong Han, Zi-Xuan Ding, Hui Zhang, Hai-Bo Yin, Gui-Zhong Xin, De-Qiang Dou, Hui-Peng Song
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Abstract

Introduction: Berberis fortunei Lindl. (BF) is a medicinal plant widely utilized in East Asia. However, the chemical components present in its roots, stems, and leaves have not been systematically analyzed and compared. The specific active ingredients that inhibit HT29 colorectal cancer cells are still unclear.

Objective: The aim of this study is to comprehensively analyze the chemical compositions of BF's roots, stems, and leaves and to evaluate their biological function against HT29 cells.

Methodology: GC-IMS and LC-QTOF-MS were employed to analyze the volatile and nonvolatile components of BF, respectively. The MTT assay was used to evaluate the inhibitory effects of extracts and compounds from BF on HT29 cells. A network analysis based on molecular docking was conducted to identify the potential targets of compounds.

Results: A total of 77 volatile components and 116 nonvolatile components were identified in the roots, stems, and leaves of BF. The inhibitory activity of different parts of BF against HT29 cells followed the order: roots > stems > leaves. Protoberberine-type alkaloids showed more pronounced effects at 24 h, whereas bisbenzylisoquinoline-type alkaloids demonstrated stronger activity at 48 h. Network analysis based on molecular docking revealed significant differences in the pathways targeted by the two types of alkaloids.

Conclusion: This study not only comprehensively analyzed the compositions of BF but also examined its biological function in inhibiting HT29 cells, laying a theoretical foundation for its further development and application. The findings provide diverse lead compounds for the subsequent development of drugs against colorectal cancer.

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通过 GC-IMS、LC-QTOF-MS 和基于 Docking 的网络分析全面分析小檗中的挥发性和非挥发性成分及其对 HT29 大肠癌细胞的抑制作用
简介:小檗。BF是东亚地区广泛使用的药用植物。然而,存在于其根、茎和叶中的化学成分尚未被系统地分析和比较。抑制HT29结直肠癌细胞的具体活性成分尚不清楚。目的:综合分析BF根、茎、叶的化学成分,评价其对HT29细胞的生物学功能。方法:采用GC-IMS和LC-QTOF-MS分别对BF的挥发性成分和非挥发性成分进行分析。采用MTT法评价BF提取物和化合物对HT29细胞的抑制作用。基于分子对接的网络分析,确定了化合物的潜在靶点。结果:共鉴定出77种挥发性成分,116种非挥发性成分。不同部位对HT29细胞的抑制作用顺序为:根>茎>叶。原小檗碱类生物碱在24 h时的活性更明显,而双苯基异喹啉类生物碱在48 h时的活性更强。基于分子对接的网络分析显示,两类生物碱的靶向途径存在显著差异。结论:本研究不仅全面分析了BF的成分,还考察了其抑制HT29细胞的生物学功能,为其进一步开发应用奠定了理论基础。这一发现为后续开发抗结直肠癌药物提供了多种先导化合物。
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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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