基于网络药理学及分子对接技术探讨柴胡-黄芪治疗酒精性肝纤维化的作用机制

doi:10.5246/jcps.2025.02.013

中国药学(英文版) ›› 2025, Vol. 34 ›› Issue (2): 163-174.DOI: 10.5246/jcps.2025.02.013

基于网络药理学及分子对接技术探讨柴胡-黄芪治疗酒精性肝纤维化的作用机制

朱晓东¹^,^#, 邸学士²^,^#, 孙劲晖³^,^*()

^1. 广西中医药大学, 广西南宁 530299
^2. 北京中医药大学, 北京 100029
^3. 北京中医药大学东直门医院, 北京 100700

收稿日期:2024-09-29 修回日期:2024-10-30 接受日期:2024-12-13 出版日期:2025-03-01 发布日期:2025-03-02
通讯作者: 孙劲晖

Deciphering the mechanism of action of Chaihu-Astragalus compound in the management of alcoholic liver fibrosis: A network pharmacology and molecular docking approach

Xiaodong Zhu¹^,^#, Xueshi Di²^,^#, Jinhui Sun³^,^*()

¹ Guangxi University of Chinese Medicine, Nanning 530299, Guangxi, China
² Beijing University of Chinese Medicine, Beijing 100029, China
³ Dongzhimen Hospital of Beijing University of Chinese Medicine, Beijing 100700, China

Received:2024-09-29 Revised:2024-10-30 Accepted:2024-12-13 Online:2025-03-01 Published:2025-03-02
Contact: Jinhui Sun
About author:
^# Xiaodong Zhu and Xueshi Di contributed equally to this work.
Supported by:
National Natural Science Foundation of China (Grant No. 81573969).

摘要/Abstract

摘要：

本研究旨在通过网络药理学和分子对接技术分析柴胡-黄芪治酒精性肝纤维化的潜在作用机制。通过TCMSP数据库筛选柴胡-黄芪的活性成分及作用靶点, 通过GeneCards数据库筛选酒精性肝纤维化的疾病相关靶点, 获取二者交集靶点, 即柴胡-黄芪治疗酒精性肝纤维化的潜在作用靶点。使用Cytoscape软件构建“中药-活性成分-交集靶点”网络, 并分析网络中的关键活性成分; 利用STRING数据库对交集靶点进行蛋白互作(PPI)网络分析, 筛选出潜在核心靶点; 运用DAVID平台对交集靶点进行GO功能和KEGG通路富集分析; 利用Schrödinger软件、Maestro平台对关键活性成分与关键靶点进行分子对接验证。结果共筛选得到26个活性成分及180个潜在作用靶点(交集靶点); 获得槲皮素、山奈酚、刺芒柄花素、异鼠李素、茵陈黄酮等关键活性化合物; 筛选得到AKT1、TP53、JUN、TNF、IL6等核心靶点; 潜在作用靶点主要富集在PI3K-Ak、TNF、MAPK等信号通路。研究表明, 柴胡-黄芪主要通过槲皮素、山柰酚等多种活性成分, 作用于AKT1、TP53、JUN等多靶点, 通过PI3K-AKT、TNF、MAPK等多条信号通路来发挥治疗酒精性肝纤维化的作用, 具有多成分、多靶点、多通路的特点。

关键词: 酒精性肝纤维化, 柴胡-黄芪, 网络药理学, 分子对接

Abstract:

The present study aimed to analyze the potential mechanism of action of Chaihu-Astragalus in treating alcoholic liver fibrosis using network pharmacology and molecular docking techniques. We initially screened the active ingredients and targets of Chaihu-Astragalus through the TCMSP database. Additionally, we identified disease-related targets associated with alcoholic liver fibrosis via the GeneCards database, subsequently obtaining the intersection targets of Chaihu-Astragalus for treating alcoholic liver fibrosis. Using Cytoscape software, we constructed a “drug-active ingredient-intersection target” network and evaluated the network’s major active ingredients. The intersection targets were then subjected to protein-protein interaction network analysis using the STRING database to identify possible core targets. GO functional and KEGG pathway enrichment analyses were conducted using the DAVID platform. Molecular docking verification of key active ingredients and core targets was performed using Schrödinger software and the Maestro platform. We identified 26 active ingredients and 180 potential targets (intersection targets). Key active compounds, such as quercetin, kaempferol, prickly mangosteen, isorhamnetin, and Areapillin, were highlighted. Core targets were also identified, including AKT1, TP53, JUN, TNF, and IL-6. Enrichment analyses revealed that potential targets were mainly associated with PI3K-Akt, TNF, MAPK, and other signaling pathways. Chaihu-Astragalus acted on multiple targets such as AKT1, TP53, and JUN primarily through various active ingredients like quercetin and kaempferol. Thus, it affected treating alcoholic liver fibrosis through multiple signaling pathways, such as PI3K-Akt, TNF, and MAPK. It demonstrated characteristics of being multi-component, multi-target, and multi-pathway in its approach.

Key words: Alcoholic liver fibrosis, Chaihu-Astragalus, Network pharmacology, Molecular docking

Supporting:

朱晓东, 邸学士, 孙劲晖. 基于网络药理学及分子对接技术探讨柴胡-黄芪治疗酒精性肝纤维化的作用机制[J]. 中国药学(英文版), 2025, 34(2): 163-174.

Xiaodong Zhu, Xueshi Di, Jinhui Sun. Deciphering the mechanism of action of Chaihu-Astragalus compound in the management of alcoholic liver fibrosis: A network pharmacology and molecular docking approach[J]. Journal of Chinese Pharmaceutical Sciences, 2025, 34(2): 163-174.

图/表 8

Table 1. Active constituents of Chaihu-Astragalus.

Figure 1. Venn diagram of the intersecting targets of Chaihu-Astragalus and AHF.

Figure 2. “Chinese herbal medicine-active ingredient-intersection target” network diagram. Note: The blue nodes represent the potential action targets of Chaihu-Astragalus for AHF treatment; the red nodes represent Chaihu and Astragalus herbal medicines; the green nodes represent the active ingredients of Chinese medicines; the orange nodes represent the active ingredients shared by Chaihu-Astragalus.

Figure 3. PPI network of target genes of Chaihu-Astragalus for AHF treatment. Note: the node size and color are adjusted according to the node degree property, and the edge thickness and color are adjusted according to the interaction strength between nodes.

Figure 4. GO enrichment analysis of key targets by Chaihu-Astragalus.

Figure 5. Enrichment of key target KEGG pathway by Chaihu-Astragalus drug.

Table 2. Molecular docking results of the key components and targets of Chaihu-Astragalus drug for the treatment of AHF.

Figure 6. Molecular docking pattern of compounds and key targets. Note: A, B show the 3D structure of AKT1, TP53 with MOL00042; C, D, E show the 3D structure of JUN, TNF, IL-6 with MOL000098; a, b shows the detailed binding pattern of active site of MOL00042 with AKT1, TP53; c, d, e shows the detailed binding pattern of MOL000098 with JUN, TNF, IL-6 active site binding pattern.

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基于网络药理学及分子对接技术探讨柴胡-黄芪治疗酒精性肝纤维化的作用机制

Deciphering the mechanism of action of Chaihu-Astragalus compound in the management of alcoholic liver fibrosis: A network pharmacology and molecular docking approach

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