Exploring the mechanism of Radix Bupleuri in the treatment of depression combined with SARS-CoV-2 infection through bioinformatics, network pharmacology, molecular docking, and molecular dynamic simulation.

IF 3.2 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM Metabolic brain disease Pub Date : 2025-01-17 DOI:10.1007/s11011-025-01536-7
Zexing Chen, Xinhua Wang, Wanyi Huang
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Abstract

Background: Radix Bupleuri is commonly used in treating depression and acute respiratory diseases such as SARS-CoV-2 infection in China. However, its underlying mechanism in treating major depressive disorder combined with SARS-CoV-2 infection remains unclear.

Aim: This study aims to elucidate the pharmacological mechanisms of Radix Bupleuri in treating major depressive disorder combined with SARS-CoV-2 infection, employing bioinformatics, network pharmacology, molecular docking, and dynamic simulation techniques.

Method: Active ingredients and drug target genes of Radix Bupleuri were collected from TCMSP, PubChem, SwissTargetPrediction, and SuperPred databases. Differentially expressed genes were analyzed using datasets of SARS-CoV-2 infection and major depression disorder from the GEO database. The key genes were identified by using GO and KEGG functional analyses and STRING database. Machine learning methods were employed to predict core target gene, and ROC curve analysis validated the models' accuracy and the core gene expression had been analyzed and validated with other datasets. Molecular docking and dynamic simulation were conducted to verify the affinity of the active ingredients with core target gene. Finally, immune infiltration and correlation analyses between core target genes and immune cells were performed.

Results: A total of 15 active ingredients, 1898 differentially expressed genes related to SARS-CoV-2 infection, and 814 differentially expressed genes related to major depression disorder were collected. 18 common genes were identified at the intersection of Radix Bupleuri, major depression disorder, and SARS-CoV-2 infection. The key gene JAK2 was identified through PPI network construction and machine learning model predictions. Molecular docking showed that the binding energies of the active ingredients with JAK2 were all below - 5 kcal/mol, with petunidin exhibiting the highest affinity. Molecular dynamic simulations further suggested stable interactions with JAK2. Immune infiltration analysis suggested that Radix Bupleuri in the context of depression combined with SARS-CoV-2 infection may promote the activation and generation of B cells, CD4 T cells, and CD8 T cells, while inhibiting the activation of mature dendritic cells, macrophages, natural killer cells, and neutrophils. Correlation analysis of JAK2 with immune cells indicated an association with macrophage activation and the inhibition of memory B cells and activated B cells.

Conclusion: The active ingredients of Radix Bupleuri may exhibit both antidepressant and antiviral pharmacological effects in the progression of major depression disorder combined with SARS-CoV-2 infection, through a mechanism closely associated with the JAK2 target.

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通过生物信息学、网络药理学、分子对接、分子动力学模拟等手段探讨柴胡治疗抑郁症合并SARS-CoV-2感染的机制。
背景:柴胡是中国治疗抑郁症和SARS-CoV-2等急性呼吸道疾病的常用药物。然而,其治疗重度抑郁症合并SARS-CoV-2感染的潜在机制尚不清楚。目的:运用生物信息学、网络药理学、分子对接、动态模拟等技术,探讨柴胡治疗重度抑郁症合并SARS-CoV-2感染的药理机制。方法:从TCMSP、PubChem、SwissTargetPrediction和SuperPred数据库中收集柴胡的有效成分和药物靶基因。使用GEO数据库中的SARS-CoV-2感染和重度抑郁症数据集分析差异表达基因。利用GO、KEGG功能分析和STRING数据库对关键基因进行鉴定。采用机器学习方法预测核心靶基因,ROC曲线分析验证了模型的准确性,并与其他数据集分析验证了核心基因的表达。通过分子对接和动态模拟验证活性成分与核心靶基因的亲和力。最后进行免疫浸润及核心靶基因与免疫细胞的相关性分析。结果:共收集到15种有效成分,1898种与SARS-CoV-2感染相关的差异表达基因,814种与重度抑郁症相关的差异表达基因。在柴胡、重度抑郁症和SARS-CoV-2感染的交叉点鉴定出18个共同基因。通过PPI网络构建和机器学习模型预测,确定了关键基因JAK2。分子对接表明,活性成分与JAK2的结合能均在- 5 kcal/mol以下,其中矮牵牛花苷的亲和力最高。分子动力学模拟进一步表明与JAK2的相互作用稳定。免疫浸润分析提示,抑郁合并SARS-CoV-2感染背景下的柴胡可促进B细胞、CD4 T细胞和CD8 T细胞的活化和生成,抑制成熟树突状细胞、巨噬细胞、自然杀伤细胞和中性粒细胞的活化。JAK2与免疫细胞的相关性分析表明,它与巨噬细胞活化、记忆B细胞和活化B细胞的抑制有关。结论:柴胡有效成分可能通过与JAK2靶点密切相关的机制,在重度抑郁症合并SARS-CoV-2感染的进展中表现出抗抑郁和抗病毒的药理作用。
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来源期刊
Metabolic brain disease
Metabolic brain disease 医学-内分泌学与代谢
CiteScore
5.90
自引率
5.60%
发文量
248
审稿时长
6-12 weeks
期刊介绍: Metabolic Brain Disease serves as a forum for the publication of outstanding basic and clinical papers on all metabolic brain disease, including both human and animal studies. The journal publishes papers on the fundamental pathogenesis of these disorders and on related experimental and clinical techniques and methodologies. Metabolic Brain Disease is directed to physicians, neuroscientists, internists, psychiatrists, neurologists, pathologists, and others involved in the research and treatment of a broad range of metabolic brain disorders.
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