Integrating network pharmacology and bioinformatics to explore the mechanism of Xiaojian Zhongtang in treating major depressive disorder: An observational study.

IF 1.3 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL
Huaning Jiang, Jian Zhang, Quan Li, Yanyan Zhou
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引用次数: 0

Abstract

Major depressive disorder (MDD) is a common mental illness. The traditional Chinese medicine compound Xiaojian Zhongtang (XJZT) has a good therapeutic effect on MDD, but the specific mechanism is not clear. The aim of this study is to explore the molecular mechanism of XJZT in the treatment of MDD through network pharmacology and bioinformatics. The traditional Chinese medicine system pharmacology database was used to screen the chemical components and targets of XJZT, while the online Mendelian inheritance in man, DisGeNET, Genecards, and therapeutic target database databases were used to collect MDD targets and identify the intersection targets of XJZT and MDD. A "drugs-components-targets" network was constructed using the Cytoscape platform, and the STRING was used for protein-protein interaction analysis of intersecting targets. Gene Ontology and Kyoto encyclopedia of genes and genomes analysis of intersecting targets was performed using the DAVID database. Obtain serum and brain transcriptome datasets of MDD from the gene expression omnibus database, and perform differentially expressed genes, weighted gene co-expression network analysis, gene set enrichment analysis, and receiver operating characteristic analysis. A total of 127 chemical components and 767 targets were obtained from XJZT, among which quercetin, kaempferol, and maltose are the core chemical components, and 1728 MDD targets were screened out, with 77 intersecting targets between XJZT and MDD. These targets mainly involve AGE-RAGE signaling pathway in diabetic complexes, epidermal growth factor receptor tyrosine kinase inhibitor resistance, and HIF-1 signaling pathway, and these core targets have strong binding activity with core components. In addition, 1166 differentially expressed genes were identified in the MDD serum transcriptome dataset, and weighted gene co-expression network analysis identified the most relevant gene modules (1269 genes), among which RAC-alpha serine/threonine-protein kinase (AKT1), D(4) dopamine receptor (DRD4), and kynurenine 3-monooxygenase (KMO) were target genes for the treatment of MDD with XJZT, these 3 genes are mainly related to the ubiquitin-mediated proteolysis, arachidonic acid (AA) metabolism, and Huntington disease pathways, and the expression of AKT1, DRD4, and KMO was also found in the MDD brain transcriptome dataset, which is significantly correlated with the occurrence of MDD. We have identified 3 key targets for XJZT treatment of MDD, including AKT1, KMO, and DRD4, and they can be regulated by the key components of XJZT, including quercetin, maltose, and kaempferol. This provides valuable insights for the early clinical diagnosis and development of therapeutic drugs for MDD.

整合网络药理学和生物信息学,探索小建中堂治疗重度抑郁障碍的机制:一项观察性研究。
重度抑郁障碍(MDD)是一种常见的精神疾病。中药复方小建中堂(XJZT)对MDD有较好的治疗效果,但具体机制尚不清楚。本研究旨在通过网络药理学和生物信息学探讨小建中堂治疗 MDD 的分子机制。利用中药系统药理学数据库筛选XJZT的化学成分和靶点,同时利用在线人类孟德尔遗传、DisGeNET、Genecards和治疗靶点数据库收集MDD靶点,确定XJZT与MDD的交叉靶点。利用Cytoscape平台构建了 "药物-成分-靶点 "网络,并利用STRING对交叉靶点进行蛋白-蛋白相互作用分析。利用 DAVID 数据库对交叉靶点进行基因本体和京都基因与基因组百科全书分析。从基因表达总括数据库中获取 MDD 的血清和脑转录组数据集,并进行差异表达基因、加权基因共表达网络分析、基因组富集分析和接收者操作特征分析。从XJZT中获得了127种化学成分和767个靶点,其中槲皮素、山奈酚和麦芽糖是核心化学成分,并筛选出1728个MDD靶点,XJZT和MDD之间有77个交叉靶点。这些靶点主要涉及糖尿病复合物中的 AGE-RAGE 信号通路、表皮生长因子受体酪氨酸激酶抑制剂抗性、HIF-1 信号通路等,这些核心靶点与核心成分具有很强的结合活性。此外,在MDD血清转录组数据集中发现了1166个差异表达基因,加权基因共表达网络分析确定了最相关的基因模块(1269个基因),其中包括RAC-α丝氨酸/苏氨酸蛋白激酶(AKT1)、D(4)多巴胺受体(DRD4)、这3个基因主要与泛素介导的蛋白酶解、花生四烯酸(AA)代谢和亨廷顿病通路有关,而且在MDD脑转录组数据集中也发现了AKT1、DRD4和KMO的表达,这3个基因的表达与MDD的发生显著相关。我们发现了XJZT治疗MDD的3个关键靶点,包括AKT1、KMO和DRD4,它们可以被XJZT的关键成分(包括槲皮素、麦芽糖和山奈酚)调控。这为MDD的早期临床诊断和治疗药物的开发提供了宝贵的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Medicine
Medicine 医学-医学:内科
CiteScore
2.80
自引率
0.00%
发文量
4342
审稿时长
>12 weeks
期刊介绍: Medicine is now a fully open access journal, providing authors with a distinctive new service offering continuous publication of original research across a broad spectrum of medical scientific disciplines and sub-specialties. As an open access title, Medicine will continue to provide authors with an established, trusted platform for the publication of their work. To ensure the ongoing quality of Medicine’s content, the peer-review process will only accept content that is scientifically, technically and ethically sound, and in compliance with standard reporting guidelines.
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