Han Li, Wei Siwen, Wang Rong, Liu Yiran, Zhong Yi, Luo Huaiqing
Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Changsha Medical University, Changsha 410219, China.
Hunan Provincial Key Laboratory of the Traditional Chinese Medicine Agricultural Biogenomics, Changsha Medical University, Changsha 410219, China.
Curr Issues Mol Biol. 2025 May 9;47(5):342. doi: 10.3390/cimb47050342.
To elucidate the molecular targets and mechanisms by which exerts therapeutic effects in major depressive disorder (MDD) using network pharmacology and molecular docking approaches.
Bioactive compounds of were identified from comprehensive pharmacological databases. MDD-related targets were sourced from extensive genomic repositories. Overlapping targets were determined and subjected to network topology and protein-protein interaction (PPI) analyses to identify core targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to reveal pertinent biological processes and signaling pathways. Molecular docking simulations validated the interactions between key bioactive compounds and core targets.
A total of 57 bioactive compounds were identified in , including apigenin, heterotropan, and isoelemicin. Integrative analysis revealed 700 compound-related targets and 2590 MDD-associated targets, with 150 intersecting targets. Network analyses pinpointed five core targets: TP53, STAT3, AKT1, PIK3CA, and PIK3R1. GO enrichment identified 858 significant biological processes, while KEGG pathway analysis highlighted 155 enriched pathways, notably the PI3K-Akt, cAMP, and MAPK signaling pathways. Molecular docking studies demonstrated strong binding affinities between key compounds and their respective targets.
This study delineates the multifaceted polypharmacological mechanisms through which may confer protective effects against major depressive disorder, underscoring its potential as a promising therapeutic agent.
运用网络药理学和分子对接方法阐明[药物名称未给出]在重度抑郁症（MDD）中发挥治疗作用的分子靶点和机制。
从综合药理学数据库中鉴定[药物名称未给出]的生物活性化合物。MDD相关靶点来自广泛的基因组库。确定重叠靶点并进行网络拓扑和蛋白质-蛋白质相互作用（PPI）分析以识别核心靶点。进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路富集分析以揭示相关的生物学过程和信号通路。分子对接模拟验证关键生物活性化合物与核心靶点之间的相互作用。
在[药物名称未给出]中总共鉴定出57种生物活性化合物，包括芹菜素、异托烷和异榄香脂素。综合分析揭示了700个化合物相关靶点和2590个MDD相关靶点，其中有150个交叉靶点。网络分析确定了五个核心靶点：TP53、STAT3、AKT1、PIK3CA和PIK3R1。GO富集鉴定出858个显著的生物学过程，而KEGG通路分析突出了155条富集通路，特别是PI3K-Akt、cAMP和MAPK信号通路。分子对接研究表明关键化合物与其各自靶点之间具有很强的结合亲和力。
本研究阐明了[药物名称未给出]可能对重度抑郁症具有保护作用的多方面多药理学机制，强调了其作为一种有前景的治疗药物的潜力。
