Therapeutic potential of Leonotis leonurus and Mentha longifolia in depression: insights from network pharmacology and molecular dynamics stimulation-based study

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 SLC6A4, PTGS2, MAOA, and MAOB were enriched in serotonergic and dopaminergic synapse pathways, neuroactive ligand–receptor interaction, and PI3K/Akt signalling, suggesting, suggesting potential involvement in neurotransmission and neuroinflammatory regulation. Molecular docking showed strong interactions of procyanidin B5 and chrysoeriol with SLC6A4 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 SLC6A4. For M. longifolia, targets such as DRD4, DRD3, GSK3β, COMT, and AKT1 were linked to dopaminergic synapse and neuroactive ligand–receptor pathways. Key compounds, including baicalin, salvianolic acid A, and rosmarinic acid, showed strong binding to DRD4, DRD3, and GSK3β. Notably, quercetin 3-galactoside exhibited the highest affinity toward DRD4 (− 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.