Exploring the antidepressant mechanisms of Coptidis Rhizoma via a network pharmacology approach: focusing on neurotransmitter, neuroplasticity, and inflammation

Objectives: This study aimed to explore the potential antidepressant mechanisms of Coptidis Rhizoma using a network pharmacology approach.Methods: Active compounds of Coptidis Rhizoma were obtained from TCMSP, and their possible targets were predicted using SwissTargetPrediction. Depression-related genes were collected from GeneCards, DisGeNet, and OMIM. Overlapping genes were used to build a protein-protein interaction network via STRING and analyzed in Cytoscape with CytoHubba. KEGG and GO enrichment analyses were conducted with the clusterProfiler package in R. Molecular docking was conducted with PyRx and Chimera to evaluate binding affinities between key targets and active compounds. A compound-target-pathway network was constructed based on key PPI nodes and enriched KEGG pathways.Results: 12 active compounds were identified from Coptidis Rhizoma, yielding 397 predicted targets. Overlap with 4,776 depression-related genes produced 243 targets for PPI network construction. Hub genes including AKT1, TNF, and DRD2 were identified. KEGG and GO analyses indicated PI3K-AKT, neuroactive ligand-receptor interaction, and MAPK signaling as major pathways. docking simulations showed significant binding affinities between key targets and active compounds.Conclusions: Coptidis Rhizoma may be associated with multiple antidepressant mechanisms, including modulation of neurotransmitter receptors, enhancement of neuroplasticity via the PI3K-AKT pathway, and suppression of inflammation via regulation of TNF and STAT3. This study provides a theoretical basis using in silico methods, and further experimental validation is warranted.