基于HPLC指纹图谱和网络药理学的白屈菜缓解IPEC-J2细胞炎性损伤作用研究

doi:10.11843/j.issn.0366-6964.2025.05.042

摘要/Abstract

摘要：

白屈菜可用于治疗多种消化道和呼吸道炎症，但其作用机制尚不明确。本研究基于指纹图谱和网络药理学预测分析白屈菜的药效成分及作用机制。采用HPLC法建立15批白屈菜指纹图谱并进行相似度评价和主成分分析；通过网络药理学方法建立白屈菜活性成分-靶点网络，分析其核心抗炎成分，通过蛋白互作网络分析其核心靶点，并进行GO和KEGG富集分析；将指纹图谱指认的共有峰与网络药理学筛选出的核心成分取交集，MTT法和ELISA法研究其对IPEC-J2细胞炎症损伤的影响。结果发现，15批次白屈菜中有12批次相似度>0.9，标定出21个共有峰，指认出其中6个分别为原阿片碱、白屈菜碱、黄连碱、血根碱、小檗碱和白屈菜红碱；网络药理学筛选出8个核心抗炎成分，分别为异紫堇定碱、(s)-金罂粟碱、(s)-氢化小檗碱、小檗碱、白屈菜碱、白屈菜红碱、氧化血根碱和(+/-)-高白屈菜碱；上述2组成分交集为白屈菜碱、小檗碱和白屈菜红碱，参考中国药典规定，选取白屈菜红碱，研究其对IPEC-J2细胞炎症的影响，发现2.5~10 μg·mL^-1白屈菜红碱能显著提高细胞存活率，显著升高IL-4和IL-10含量，降低NO、IL-1β、IL-6、IL-8、TNF-α和TGF-β1含量。综上，本研究建立了白屈菜HPLC指纹图谱，结合网络药理学方法初步揭示了白屈菜的药效成分及作用机制，为其质量控制与深入开发提供参考。

关键词: 白屈菜, 指纹图谱, 网络药理学, 白屈菜红碱, 抗炎作用

Abstract:

Chelidonium majus can be used to treat various digestive and respiratory tract inflammations, but its mechanism of action is still unclear. This study predicts and analyzes the pharmacodynamic components and mechanisms of C. majus using fingerprint and network pharmacology. A total of 15 batches of C. majus fingerprint were established using HPLC and evaluated for similarity and principal component analysis. A network of active components and targets of C. majus was established using network pharmacology methods. The core anti-inflammatory components were analyzed, along with the core targets through protein interaction network analysis, followed by GO enrichment and KEGG enrichment analysis. The common peaks identified by fingerprint and the core components filtered by network pharmacology were intersected. The effects of C. majus on IPEC-J2 cell inflammation damage were studied using MTT and ELISA methods. The results showed that 12 out of 15 batches of C. majus had a similarity >0.9, with 21 common peaks identified, among which 6 were identified as protopine, chelidonine, coptisine, sanguinarine, berberine, and chelerythrine. Network pharmacology filtered out 8 core anti-inflammatory components, namely thalictriline, (s)-thalictroidine, (s)-tetrahydropalmatine, berberine, chelidonine, chelerythrine, oxidized sanguinarine, and (+/-)-thalicarpine. The intersection of these two sets of components was chelidonine, berberine, and chelerythrine. Referring to the regulations of the Chinese Pharmacopoeia, chelerythrine was selected for a study on its effect on IPEC-J2 cell inflammation. The study found that chelerythrine at concentrations of 2.5 to 10 μg·mL^-1 could significantly improve cell survival rate, increase the content of IL-4 and IL-10, and decrease the content of NO, IL-1β, IL-6, IL-8, TNF-α, and TGF-β1. This study has established the HPLC fingerprint of C. majus and preliminarily revealed its pharmacodynamic components and mechanisms of action using network pharmacology methods. This provides a reference for its quality control and further development.

Key words: Chelidonium majus, fingerprint, network pharmacology, chelerythrine, anti-inflammatory

中图分类号:

S853.74

陈泽晗, 张偌益, 林惠莹, 曾春丽, 林福, 李健. 基于HPLC指纹图谱和网络药理学的白屈菜缓解IPEC-J2细胞炎性损伤作用研究[J]. 畜牧兽医学报, 2025, 56(5): 2466-2480.

CHEN Zehan, ZHANG Ruoyi, LIN Huiying, ZENG Chunli, LIN Fu, LI Jian. Anti-inflammatory Effects of Chelidonium majus on IPEC-J2 Cells based on HPLC Fingerprint and Network Pharmacology[J]. Acta Veterinaria et Zootechnica Sinica, 2025, 56(5): 2466-2480.

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编号 No.	产地 Place of production	编号 No.	产地 Place of production	编号 No.	产地 Place of production
S1	辽宁	S6	江西	S11	云南
S2	吉林	S7	浙江	S12	安徽
S3	河北	S8	四川	S13	广西
S4	河南	S9	陕西	S14	湖北
S5	江苏	S10	黑龙江	S15	福建

成分Ingredient	回归方程Regression equation	r²
原阿片碱Protopine	y=13 796x+4 626.2	0.999 3
白屈菜碱Chelidonine	y =4 476.4x+6 751.9	0.999 0
黄连碱Coptisine	y=22 512x+7 186.9	0.999 8
血根碱Sanguinarine	y=29 031x-1 564.4	0.999 9
小檗碱Berberine	y=23 151x+5.896	0.999 8
白屈菜红碱 Chelerythrine	y=54 706x-1 948	0.999 9

编号 No.	S1	S2	S3	S4	S5	S6	S7	S8
S1	1.000	0.981	0.995	0.964	0.991	0.973	0.990	0.691
S2	0.981	1.000	0.987	0.986	0.990	0.987	0.989	0.740
S3	0.995	0.987	1.000	0.975	0.997	0.981	0.998	0.724
S4	0.964	0.986	0.975	1.000	0.982	0.998	0.981	0.762
S5	0.991	0.990	0.997	0.982	1.000	0.984	0.999	0.734
S6	0.973	0.987	0.991	0.998	0.994	1.000	0.984	0.752
S7	0.990	0.931	0.999	0.930	0.997	0.983	1.000	0.106
S8	0.691	0.143	0.071	0.167	0.106	0.147	0.106	1.000
S9	0.554	0.631	0.585	0.677	0.601	0.663	0.603	0.946
S10	0.179	0.211	0.194	0.241	0.191	0.242	0.196	0.750
S11	0.993	0.987	0.994	0.982	0.996	0.986	0.994	0.721
S12	0.971	0.987	0.980	0.998	0.984	0.999	0.984	0.755
S13	0.980	0.992	0.987	0.965	0.993	0.995	0.992	0.746
S14	0.986	0.994	0.992	0.992	0.996	0.993	0.995	0.742
S15	0.987	0.992	0.991	0.993	0.994	0.996	0.993	0.737

编号 No.	S9	S10	S11	S12	S13	S14	S15	对照指纹图谱 Control fingerprint
S1	0.554	0.179	0.993	0.971	0.980	0.986	0.987	0.968
S2	0.631	0.211	0.987	0.987	0.992	0.994	0.992	0.983
S3	0.585	0.194	0.994	0.980	0.987	0.992	0.991	0.979
S4	0.677	0.241	0.982	0.998	0.995	0.992	0.993	0.987
S5	0.601	0.191	0.996	0.984	0.993	0.996	0.994	0.982
S6	0.663	0.242	0.986	0.999	0.995	0.993	0.996	0.988
S7	0.043	0.995	0.910	0.984	0.992	0.995	0.993	0.983
S8	0.389	0.105	0.176	0.755	0.746	0.742	0.737	0.832
S9	1.000	0.817	0.596	0.666	0.645	0.632	0.631	0.734
S10	0.817	1.000	0.194	0.245	0.211	0.208	0.209	0.354
S11	0.596	0.194	1.000	0.985	0.991	0.995	0.994	0.980
S12	0.666	0.245	0.985	1.000	0.995	0.993	0.995	0.988
S13	0.645	0.211	0.991	0.995	1.000	0.998	0.999	0.987
S14	0.632	0.208	0.995	0.993	0.998	1.000	0.998	0.988
S15	0.631	0.209	0.994	0.995	0.999	0.998	1.000	0.987

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