基于网络药理学和分子对接探究绿原酸缓解鸡肠道炎症的作用机制

doi:10.3864/j.issn.0578-1752.2025.03.014

摘要/Abstract

摘要：

【目的】利用网络药理学和分子对接方法，预测绿原酸缓解鸡肠道炎症的作用机制，为绿原酸的应用提供参考。【方法】使用中药系统药理学数据库、DisGeNET数据库以及Gene Cards数据库，检索“Caffeoylquinic acid”“Intestinal inflammation”，获得绿原酸、肠道炎症相关靶点，并获取交集靶点集。使用 Cytoscape 3.10 中 CytoNCA 程序计算网络节点中心性，筛选关键绿原酸单体。利用 STRING 数据库构建针对鸡肠道炎症的靶点蛋白互作网络，利用 David 数据库对交集靶点进行基因本体（GO）功能和京都基因与基因组百科全书（KEGG）通路富集分析。此外，对以上靶点进行分子复合物检测分析（MCODE）得到核心基因簇，构建绿原酸-靶点-信号通路网络。使用 Autodock vina将筛选的关键绿原酸单体与核心靶点进行分子对接，并将结果可视化。【结果】TCMSP 数据库检索得到绿原酸靶点222个，DisGeNET和Gene Cards数据库质控后获得肠道炎症靶点1 453个，获得二者的交集靶点78个。鸡肠道炎症靶点 PPI 网络的节点数为 53，边数为162。核心靶点分别为非受体酪氨酸激酶（non-receptor tyrosine kinase，SRC）、胱天蛋白酶3 （caspase-3，CASP3）、基质金属蛋白酶9（matrix metalloprotein-9，MMP9）、表皮生长因子受体（epithelial growth factor receptor，EGFR）、雌激素受体1 （estrogen receptor 1，ESR1）、基质金属蛋白酶2（matrix metalloprotein-2，MMP2）、丝氨酸/苏氨酸激酶（serine/threonine kinases，BRAF）、激酶插入域蛋白受体（kinase insert domain receptor，KDR）、丝裂原活化蛋白激酶3（mitogen-activated protein kinase 3，MAPK3），分子对接结果显示关键绿原酸单体与上述核心靶点均可稳定结合。GO 功能富集分析（P<0.05）共获得87 种生物学过程（biological processes，BP）、20种细胞组分（cellular components，CC）和35 种分子功能（molecular functions，MF），KEGG 共富集到 26 条信号通路， MCODE 分析得到两个主要基因簇。【结论】通过交叉验证和文献支持预测绿原酸可能通过MAPK、C-型凝集素和Focal adhesion等途径调节炎症反应，缓解鸡肠道炎症；此外，新绿原酸和异绿原酸A两种单体，可能在缓解鸡肠道炎症中发挥关键作用。研究利用网络药理学和分子对接方法挖掘了绿原酸缓解鸡肠道炎症的潜力，为富含绿原酸的植物以及绿原酸单体在鸡生产上的应用提供了理论参考。

关键词: 绿原酸, 鸡, 肠道炎症, 网络药理学, 分子对接

Abstract:

【Objective】The study aimed to predict the mechanisms of chlorogenic acid in alleviating intestinal inflammation in chickens by using network pharmacology and molecular docking, so as to provide the reference for the application of chlorogenic acid. 【Method】 Firstly, "caffeoylquinic acid" and "intestinal inflammation" were retrieved from the TCMSP, DisGeNET database, and Gene Cards database, respectively, to obtain targets related to chlorogenic acid and intestinal inflammation. Venn intersection was used to obtain the target set of chlorogenic acid for alleviating intestinal inflammation. CytoNCA program in Cytoscape 3.10 was used to calculate network node centrality and to screen for key chlorogenic acid monomers. A protein-protein interaction (PPI) network targeting intestinal inflammation in chicken was constructed by using the STRING database, and gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on intersecting targets were carried out using the David database. In addition, the molecular complex detection analysis (MCODE) was performed on the above targets to obtain core gene clusters, and a chlorogenic acid target signaling pathway network was constructed. Autodock vina was employed to perform molecular docking between the selected key chlorogenic acid monomers and core targets, and the results were visualized by using the Pymol software. 【Result】 222 chlorogenic acid targets were retrieved from the TCMSP database, 1 453 targets for intestinal inflammation were obtained after quality control in the DisGeNET and Gene Caeds databases, and 78 chlorogenic acid targets in alleviating intestinal inflammation were obtained. The target PPI network for intestinal inflammation in chickens had 53 nodes and 162 edges. The core targets were SRC (Non-receptor tyrosine kinase), CASP3 (Apoptotic protease 3), MMP9 (Matrix metalloprotein-9), EGFR (Epithelial growth factor receptor), ESR1 (Estrogen receptor 1), MMP2 (Matrix metalloprotein- 2), BRAF (Serine/threonine kinase), KDR (Kinase insertion domain protein receptor), and MAPK3 (Mitogen activated protein kinase 3). Molecular docking results showed that the key chlorogenic acid monomers could stably bind to the core targets mentioned above. GO functional enrichment analysis (P<0.05) revealed 87 Biological processes (BP), 20 Cellular components (CC), and 35 Molecular functions (MF). KEGG enriched 26 signaling pathways, while MCODE analysis revealed two major gene clusters. 【Conclusion】Through cross validation and literature support, it was predicted that chlorogenic acid might regulate inflammatory response and alleviate intestinal inflammation in chicken through pathways, such as MAPK, C-type lectin, and Focal adhesion. In addition, two monomers, including neochlorogenic acid and isochlorogenic acid A, might play a crucial role in alleviating intestinal inflammation. This study utilized network pharmacology and molecular docking methods to explore the potential of stevia chlorogenic acid in alleviating intestinal inflammation in chickens, providing theoretical reference for the application of chlorogenic acid and plants rich in chlorogenic acid monomers in production.

Key words: chlorogenic acid, chicken, intestinal inflammation, network pharmacology, molecular docking

姚宏, 施寿荣, 赵茹茜. 基于网络药理学和分子对接探究绿原酸缓解鸡肠道炎症的作用机制[J]. 中国农业科学, 2025, 58(3): 600-616.

YAO Hong, SHI ShouRong, ZHAO RuQian. The Potential and Mechanism of Chlorogenic Acid to Alleviate Intestinal Inflammation in Chickens Based on Network Pharmacology and Molecular Docking[J]. Scientia Agricultura Sinica, 2025, 58(3): 600-616.

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成分名称 Ingredient name	中介中心性 Betweenness	点度中心性 Degree
新绿原酸（3-CQA）	1536.21	46
隐绿原酸（4-CQA）	1249.20	44
绿原酸（5-CQA）	1165.79	43
异绿原酸A（3,5-DICQA）	2155.89	36
异绿原酸B（3,4-DICQA）	1341.03	36
异绿原酸C（4,5-DICQA）	1251.88	31

序号 Serial number	基因 Gene	名称 Name
1	SRC	非受体酪氨酸激酶Non-receptor tyrosine kinase
2	CASP3	细胞凋亡蛋白酶3 Caspase-3
3	MMP9	基质金属蛋白酶9 Matrix metalloproteinase 9
4	EGFR	表皮生长因子受体 Epidermal growth factor receptor
5	ESR1	雌激素受体1 Estrogen Receptor 1
6	MMP2	基质金属蛋白酶2 Matrix metalloproteinase 2
7	BRAF	丝氨酸/苏氨酸激酶Serine/threonine kinase
8	KDR	激酶插入域蛋白受体Kinase insert domain receptor
9	MAPK3	丝裂原活化蛋白激酶3 Mitogen-activated protein kinase 3

基因簇 Gene cluster	GO条目 GO Term	描述 Description	Log₁₀(P)
Cluster 1	GO:0070374	ERK1和ERK2级联正调控Positive regulation of ERK1 and ERK2 cascade	-5.24
	GO:0007169	跨膜受体蛋白酪氨酸激酶信号通路Transmembrane receptor protein tyrosine kinase signaling pathway	-5.15
	GO:0006468	蛋白质磷酸化Protein phosphorylation	-4.79
Cluster 2	GO:0007596	血液凝结Blood coagulation	-3.90
	GO:0030194	凝血正调控Positive regulation of blood coagulation	-2.96
	GO:0048771	组织重塑Tissue remodeling	-2.96

配体 Ligand	受体 Receptor	结合自由能 Binding free energy (kcal·mol^-1)
3-CQA	SRC	-6.5
	CASP3	-7.6
	MMP9	-6.4
	EGFR	-8.0
	ESR1	-7.1
	MMP2	-7.5
	BRAF	-6.7
	KDR	-6.0
	MAPK3	-8.1
3,5-CQA	SRC	-8.7
	CASP3	-7.9
	MMP9	-8.6
	EGFR	-9.1
	ESR1	-7.8
	MMP2	-9.1
	BRAF	-7.9
	KDR	-6.4
	MAPK3	-9.3