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网络药理学分析结合实验验证探索五味子合剂治疗糖尿病肾病的作用机制。

Network pharmacology analysis combined with experimental validation to explore the therapeutic mechanism of Schisandra Chinensis Mixture on diabetic nephropathy.

机构信息

Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, 100078, China.

Beijing University of Chinese Medicine, Beijing, 100029, China.

出版信息

J Ethnopharmacol. 2023 Feb 10;302(Pt A):115768. doi: 10.1016/j.jep.2022.115768. Epub 2022 Oct 22.


DOI:10.1016/j.jep.2022.115768
PMID:36280016
Abstract

ETHNOPHARMACOLOGICAL RELEVANCE: Diabetic nephropathy (DN) is one of the most common and serious microvascular complications of Diabetes mellitus (DM). The inflammatory response plays a critical role in DN. Schisandra Chinensis Mixture (SM) has shown promising clinical efficacy in the treatment of DN while the pharmacological mechanisms are still unclear. AIM OF THE STUDY: In this study, a network pharmacology approach and bioinformatic analysis were adopted to predict the pharmacological mechanisms of SM in DN therapy. Based on the predicted results, molecular docking and in vivo experiments were used for verification. MATERIALS AND METHODS: In this study, the candidate bioactive ingredients of SM were obtained via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and supplementing according to the literature. SM putative targets and the verified targets were acquired from TCMSP and SiwssTartgetPrediction Database. DN-related target genes were collected from GeneCards, OMIM, DisGeNET databases, and microarray data analysis. Biological function and pathway analysis were performed to further explore the pharmacological mechanisms of SM in DN therapy. The protein-protein interaction (PPI) network was established to screen the hub gene. The Receiver Operating Characteristic (ROC) analysis and the molecular docking simulations were performed to validate the potential target-drug interactions. The fingerprint spectrum of multi-components of the SM was characterized by UPLC-MS/MS. The signaling pathways associated with inflammation and hub genes were partially validated in SD rats. RESULTS: A total of 36 bioactive ingredients were contained, and 666 component-related targets were screened from SM, of which 50 intersected with DN targets and were considered potential therapeutic targets. GO analyses revealed that the 50 intersection targets were mainly enriched in the inflammatory response, positive regulation of angiogenesis, and positive regulation of phosphatidylinositol 3-kinase(PI3K) signaling. KEGG analyses indicated that the PI3K-Akt signaling pathway was considered as the most important pathway for SM antagonism to the occurrence and development of DN, with the highest target count enrichment. PPI network results showed that the top 15 protein targets in degree value, VEGFA, JAK2, CSF1R, NOS3, CCR2, CCR5, TLR7, FYN, BTK, LCK, PLAT, NOS2, TEK, MMP1 and MCL1, were identified as hub genes. The results of ROC analysis showed that VEGFA and NOS3 were valuable in the diagnosis of DN. The molecular docking confirmed that the core bioactive ingredients had well-binding affinity for VEGFA and NOS3. The in vivo experiments confirmed that SM significantly inhibited the over-release of inflammatory cytokines such as interleukin (IL)-6 and tumor necrosis factor receptor (TNF)-α in DN rats, while regulating the PI3K-AKT and VEGFA-NOS3 signaling pathways. CONCLUSION: This study revealed the multi-component, multi-target and multi-pathway characteristics of SM therapeutic DN. SM inhibited the inflammatory response and improved renal pathological damage in DN rats, which was related to the regulation of the PI3K-Akt and VEGFA-NOS3 signaling pathways.

摘要

民族药理学相关性:糖尿病肾病(DN)是糖尿病(DM)最常见和最严重的微血管并发症之一。炎症反应在 DN 中起着关键作用。五味子混合物(SM)在治疗 DN 方面显示出有希望的临床疗效,但其药理机制尚不清楚。

研究目的:本研究采用网络药理学方法和生物信息学分析预测 SM 治疗 DN 的药理机制。基于预测结果,采用分子对接和体内实验进行验证。

材料与方法:本研究通过中药系统药理学数据库(TCMSP)和文献补充获得 SM 的候选生物活性成分。SM 假定靶点和已验证靶点从 TCMSP 和 SiwssTartgetPrediction 数据库中获得。DN 相关靶基因从 GeneCards、OMIM、DisGeNET 数据库和微阵列数据分析中收集。进行生物功能和通路分析,以进一步探讨 SM 治疗 DN 的药理机制。建立蛋白质-蛋白质相互作用(PPI)网络,筛选关键基因。进行接收者操作特征(ROC)分析和分子对接模拟,以验证潜在的靶标-药物相互作用。采用 UPLC-MS/MS 对 SM 的多成分指纹图谱进行特征描述。在 SD 大鼠中部分验证与炎症和关键基因相关的信号通路。

结果:共包含 36 种生物活性成分,从 SM 中筛选出 666 种与成分相关的靶点,其中 50 个与 DN 靶点交叉,被认为是潜在的治疗靶点。GO 分析表明,50 个交集靶点主要富集于炎症反应、血管生成的正调控和磷脂酰肌醇 3-激酶(PI3K)信号的正调控。KEGG 分析表明,PI3K-Akt 信号通路被认为是 SM 拮抗 DN 发生和发展的最重要通路,靶基因计数最高。PPI 网络结果表明,在程度值中排名前 15 的蛋白靶标为 VEGFA、JAK2、CSF1R、NOS3、CCR2、CCR5、TLR7、FYN、BTK、LCK、PLAT、NOS2、TEK、MMP1 和 MCL1,被鉴定为关键基因。ROC 分析结果表明,VEGFA 和 NOS3 可用于诊断 DN。分子对接证实核心生物活性成分与 VEGFA 和 NOS3 具有良好的结合亲和力。体内实验证实,SM 可显著抑制 DN 大鼠中白细胞介素(IL)-6 和肿瘤坏死因子受体(TNF)-α等炎症细胞因子的过度释放,同时调节 PI3K-AKT 和 VEGFA-NOS3 信号通路。

结论:本研究揭示了 SM 治疗 DN 的多成分、多靶点和多通路特征。SM 通过调节 PI3K-Akt 和 VEGFA-NOS3 信号通路,抑制 DN 大鼠的炎症反应,改善肾脏病理损伤。

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