Therapeutic potential of Leonotis leonurus and Mentha longifolia in depression: insights from network pharmacology...

Medicinal plants offer promising multi-target therapeutic agents due to their diverse bioactive compounds. This study explored LC-MS profiling, network pharmacology, molecular docking, and molecular dynamics simulation to investigate the potential antidepressant-related mechanisms of Leonotis leonurus and Mentha longifolia. A total of 20 and 15 compounds were identified in L. leonurus and M. longifolia, respectively. Target prediction and overlap analysis revealed 16 and 22 depression-associated targets for each plant. These targets were used to construct protein-protein interaction networks and perform Gene Ontology and KEGG pathway enrichment analyses. For L. leonurus, the key targets included SLC ₆ A ₄, PTGS ₂, MAOA, and MAOB were enriched in serotonergic and dopaminergic synapse pathways, neuroactive ligand-receptor interaction, and PI ₃ K/Akt signalling, suggesting, suggesting potential involvement in neurotransmission and neuroinflammatory regulation. Molecular docking showed strong interactions of procyanidin B5 and chrysoeriol with SLC ₆ A ₄ and MAOA, respectively, while baicalin demonstrated the most favourable binding affinity (- 39.45 kcal/mol), exceeding that of fluoxetine (- 14.69 kcal/mol), both surpassing fluoxetine's affinity (- 14.69 kcal/mol) to SLC ₆ A ₄. For M. longifolia, targets such as DRD ₄, DRD ₃, GSK ₃ β, COMT, and AKT ₁ were linked to dopaminergic synapse and neuroactive ligand-receptor pathways. Key compounds, including baicalin, salvianolic acid A, and rosmarinic acid, showed strong binding to DRD ₄, DRD ₃, and GSK ₃ β. Notably, quercetin 3-galactoside exhibited the highest affinity toward DRD ₄ (- 46.74 kcal/mol), outperforming fluoxetine (- 24.91 kcal/mol). Collectively, these findings suggest that both plants may possess antidepressant-related potential through predicted multi-component, multi-target modulation of neurotransmitter systems and neuroinflammatory pathways. However, these findings remain computational and require experimental validation to confirm biological efficacy and therapeutic relevance. This study provides a mechanistic framework to support future pharmacological investigations into the traditional use of these medicinal plants for mental health applications.

The online version contains supplementary material available at 10.1007/s40203-026-00689-2.