桃红四物汤改善动静脉内瘘失功的潜在机制: 一项网络药理学、分子对接以及分子动力学模拟研究

doi:10.5246/jcps.2024.06.038

摘要/Abstract

摘要：

动静脉内瘘(AVF)失功与血液透析患者的临床预后呈负相关。本研究旨在通过网络药理学探索桃红四物汤改善AVF通畅性的潜在机制, 并通过分子对接及分子动力学模拟技术进行验证。通过TCMSP、TCMIP以及SwissTargetPrediction数据库获取桃红四物汤的活性成分及其潜在靶点, AVF失功相关的靶点则通过OMIM、DisGeNET及GeneCards数据库筛选。利用Cytoscape软件构建药物-活性成分-靶点网络, 并通过STRING平台构建蛋白质相互作用网络。GO与KEGG信号通路富集通过Metascape数据库实现。采用AutoDock软件进行核心成分与疾病靶点的分子对接, 并通过PyMOL实现图像可视化。利用GROMACS软件对核心成分-靶点复合物进行分子动力学模拟以验证其稳定性。共获得桃红四物汤66个活性成分与769个潜在靶点, 以及疾病相关靶点87个, 筛选的核心化学成分为gibberellin A120、gibberellin A30、kaempferola、paeoniflorin, 主要作用靶点为TNF-α、IL6、VEGFA和MMP9。信号通路富集表明桃红四物汤改善AVF失功的潜在机制主要为减轻炎症、调节流体剪切应力、以及改善细胞外基质重塑。分子对接提示核心成分与治疗靶点能自发结合, 分子动力学模拟同样证实成分-靶点复合物的稳定性。研究表明, 桃红四物汤可能通过改善炎症、流体剪切力、以及细胞外基质重塑改善AVF通畅性, 为桃红四物汤的临床应用提供了分子学基础。

关键词: 桃红四物汤, 动静脉内瘘, 网络药理学, 分子对接, 分子动力学模拟

Abstract:

Arteriovenous fistula (AVF) failure poses a significant prognostic challenge for patients undergoing hemodialysis. This study aimed to elucidate the mechanisms underlying the potential therapeutic effects of Taohong Siwu Decoction (TSD) in addressing AVF failure. A comprehensive approach integrating network pharmacology, molecular docking, and dynamic simulation was employed to validate it. The active constituents and putative targets of TSD were acquired from the Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicine Integrative Platform (TCMIP), and SwissTargetPrediction databases. Targets relevant to AVF failure were retrieved from the Online Mendelian Inheritance in Man (OMIM), DisGeNET, and GeneCards databases. The construction of the herb-ingredient-target network and protein-protein interaction (PPI) network was carried out using Cytoscape. Furthermore, we performed GO and KEGG enrichment analyses using the Metascape database. Molecular docking was executed with AutoDock, and results were visualized via PyMOL software. Additionally, molecular dynamics simulations were conducted using GROMACS. In this comprehensive analysis, we identified a total of 66 active ingredients and 769 potential targets, which subsequently led us to identify 87 targets closely associated with AVF failure. Notably, 10 key ingredients and 15 core targets were singled out. Among the pivotal constituents were gibberellin A120, gibberellin A30, kaempferol, and paeoniflorin, while core targets included TNF-α, IL-6, VEGFA and MMP9. Enrichment analyses, encompassing GO and KEGG, illuminated that TSD’s potential therapeutic effects in addressing AVF failure might hinge on the modulation of inflammation, shear stress, and extracellular matrix remodeling. Furthermore, molecular docking investigations and dynamic simulations corroborated strong binding interactions between the key active constituents and the core targets. Consequently, it is plausible that TSD may enhance AVF patency primarily by regulating processes related to inflammation, shear stress, and extracellular matrix remodeling. These findings constitute a solid molecular rationale for the application of TSD in the context of AVF failure.

Key words: Taohong Siwu Decoction, Arteriovenous fistula, Network pharmacology, Molecular docking, Molecular dynamic simulation

Supporting:

韩世盛, 王怡. 桃红四物汤改善动静脉内瘘失功的潜在机制: 一项网络药理学、分子对接以及分子动力学模拟研究[J]. 中国药学(英文版), 2024, 33(6): 511-524.

Shisheng Han, Yi Wang. Elucidating the mechanisms underlying Taohong Siwu Decoction in preventing arteriovenous fistula failure: A comprehensive study combining network pharmacology, molecular docking, and dynamic simulation[J]. Journal of Chinese Pharmaceutical Sciences, 2024, 33(6): 511-524.

图/表 9

Table 1. Databases and software used in this study.

Figure 1. Potential targets of TSD for preventing AVF failure. AVF: arteriovenous fistula; TSD: Taohong Siwu decoction.

Table 2. Core targets of TSD for AVF failure.

Figure 2. The herb-active component-core targets network (HH: Honghua; DH: Shudihuang; TR: Taoren; BS: Baishao; DG: Danggui; CX: Chuanxiong; HB: the common component of Honghua and Baishao; DC: the common component of Danggui and Chuanxiong). The size of the graph gradually changed from large to small according to the degree. The larger the degree value was, the more important role the part played in the network.

Table 3. Core ingredients of the TSD for AVF failure.

Figure 3. The enrichment results of GO analysis and KEGG pathway.

Table 4. The binding energy of active components with core targets.

Figure 4. Molecular docking map. (A) Gibberellin A120-IL6; (B) Gibberellin A30-MMP9; (C) Kaempferol-TNF-α; (D) Paeoniflorin-VEGF.

Figure 5. MD simulations. (A) Root mean square distances; (B) Root mean square fluctuation.

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