Combining network pharmacology, machine learning, molecular docking, molecular simulation dynamics and experimental
Xinyu Zhou1, Yan Gao2, Sashuang Liu1
1Department of Medical Psychology and Ethics, School of Basic Medicine Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, PR China.
Background:
Major depressive disorder (MDD) is a severe psychophysiological condition characterized by cognitive decline, low energy, weight loss, insomnia, and increased suicide risk, posing a significant burden on global health. Zhenwu decoction (ZWD), a traditional Chinese medicine, has shown therapeutic potential in alleviating MDD symptoms. However, its complex composition has limited the understanding of its underlying pharmacological mechanisms. This study aimed to explore the antidepressant mechanisms of ZWD in the treatment of MDD.
Methods:
Active compounds and potential targets of ZWD were identified through database screening and network pharmacology analysis. These targets were intersected with MDD-related genes to construct a protein-protein interaction network. Core targets were further refined using random forest algorithms. Molecular docking and molecular dynamics simulations were employed to evaluate the binding affinity and stability between key compounds and core targets. Experimental validation was conducted in a lipopolysaccharide (LPS)-induced mice model of depression using behavioral testing, measurement of inflammatory cytokines, and gene expression analysis.
Results:
Network pharmacology and machine learning identified TNF-α signaling as key pathways in the antidepressant effects of ZWD. Enrichment analysis highlighted the involvement of Lipid and atherosclerosis, the IL-17 signaling pathway. Core targets, including PPARG, F10, AR, TNF, PIK3CG, ADH1C, and GABRA6, were predicted to mediate its effects. Molecular docking and dynamics simulations confirmed strong binding of ZWD components, especially kaempferol, to TNF-α, inhibiting its expression. In vivo, ZWD improved anxiety/depressive-like behaviors in LPS-treated mice, evidenced by better performance in the behavioral tests. ZWD also reduced neuroinflammation, with decreased Tnf-α levels, and reduced IBA-1 and GFAP staining, indicating reduced microglial and astrocyte activation. These results suggest that ZWD alleviates depression through modulation of TNF-α-mediated inflammation.
Conclusions:
These findings suggest that ZWD exerts antidepressant effects primarily by modulating TNF-α-mediated inflammatory pathways, providing a comprehensive molecular and experimental framework supporting its clinical potential in MDD treatment.
