Comparative network pharmacology analysis of ketamine and xanomeline in major depressive disorder: Shared and distinct molecular mechanisms.

Major depressive disorder (MDD) is a leading cause of disability worldwide, and currently available antidepressants remain limited by delayed onset of action, incomplete response, and adverse effects. Ketamine is a rapid-acting antidepressant, whereas xanomeline, an M1/M4 muscarinic receptor agonist, may represent a mechanistically distinct non-monoaminergic strategy. However, the molecular basis by which xanomeline may influence depression-related pathways, and its relationship to ketamine, remain unclear. We used network pharmacology and molecular docking to compare the shared and distinct molecular mechanisms of xanomeline and ketamine in MDD. Potential drug targets were collected from public databases and intersected with MDD-related targets. Protein-protein interaction analysis was performed to identify hub genes, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Drug-pathway-target-disease networks were constructed, and shared core targets were further evaluated by molecular docking. We identified 368 overlapping targets for xanomeline-MDD and 714 for ketamine-MDD. Three KEGG pathways were shared between the two networks: EGFR tyrosine kinase inhibitor resistance, Ras signaling, and Rap1 signaling. EGFR, insulin-like growth factor 1 receptor (IGF1R), and SRC proto-oncogene, non-receptor tyrosine kinase, emerged as common core targets. Xanomeline was more strongly associated with receptor tyrosine kinase and PI3K/AKT-related signaling, whereas ketamine was more strongly linked to synaptic transmission, NMDA receptor-related functions, and glutamatergic signaling. Molecular docking supported structurally plausible binding of both drugs to EGFR, IGF1R, and SRC. These findings suggest partial convergence on downstream plasticity-related signaling nodes despite distinct upstream mechanisms and warrant further experimental investigation. However, the results should be interpreted as hypothesis-generating rather than as evidence of shared functional target engagement.