Background and Objective: Depression is one of the most frequent mental illnesses all over the world. Gastrodiae rhizoma (GR) has been used as both herbal medicine and functional food in China. Herein, we aim to decipher the pharmacological targets and active components of GR against depression by using network pharmacology, bioinformatic analysis and molecular docking. Materials and Methods: GR active components were screened based on in silico prediction models of pharmacological properties. The potential targets of GR active components were predicted. Protein-protein interaction networks were constructed using the STRING database. Hub genes were identified by the cytoHubba plugin in Cytoscape. Functional enrichment analysis were carried out using the “clusterProfiler” package in R software. Molecular docking simulation was conducted to evaluate the binding affinity between the active components and hub targets. Results: A total of 24 active components and 38 targets were identified to interpret the anti-depressive effect GR. Functional enrichment analysis showed that the anti-depressive activity of GR may be associated with various biological processes such as regulation of neurotransmitter levels and monoamine transport, as well as multiple pathways such as neuroactive ligand-receptor interaction and dopaminergic synapse. SLC6A3, SLC6A4, CNR1 and MAOA were identified as hub targets and they had a good binding ability with the GR active components. (-)-Variabilin, bis-(4-hydroxybenzyl) sulfide and 6-ethoxysanguinarine may be promising anti-depressive leading compounds. Conclusion: This study uncovers the synergistic anti-depressive effect of multiple active components in GR and provides a scientific basis for developing GR as complementary medicine or functional food in depression prevention and treatment. PDFFulltextXMLReferencesCitation
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Zhijun Xiao, Cuicui Liu, Jingjing Duan, Ting Zhou, Xiufeng Liu, Saihua Lu, Zhen Yang and Feng Xu, 2020. Pharmacological Targets and Active Components of Gastrodiae rhizoma Against Depression: Findings of Network Pharmacology. International Journal of Pharmacology, 16: 500-513.