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Our study aimed to use computational biology to understand the mechanisms for the similarities and differences in efficacies and side effects of these drugs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Potential targets for MDD and the three drugs were obtained using public databases. Venn diagrams and protein\u2013protein interaction (PPI) networks were constructed. Drug\u2010target\u2010pathway (D\u2010T\u2010P) networks were built using Cytoscape, and core targets were filtered using CytoNCA and CytoHubba plugins. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery. Ligand compounds and receptor proteins were processed with PyMOL and AutoDock. The binding of amitriptyline, mirtazapine, and escitalopram with core targets was predicted by molecular docking using AutoDock Vina. The results were visualized using PyMOL and protein\u2013ligand interaction profiler (PLIP).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Forty\u2010eight overlapping targets and 66, 50, and 30 individual targets for MDD treatment were identified for amitriptyline, mirtazapine, and escitalopram, respectively. Critical pathways included \u201cNeuroactive ligand\u2013receptor interaction,\u201d \u201cCalcium signaling pathway,\u201d and \u201cSerotonergic synapse.\u201d Key targets, indicating a wide range of effects on cellular activities and signaling mechanisms, included D(2) dopamine receptor (DRD2), CYP2D6, monoamine oxidase type B (MAOB), solute carrier family 6 member 3 (SLC6A3), solute carrier family 6 member 4 (SLC6A4), 5\u2010hydroxytryptamine receptor 2C (HTR2C), and CHRNA4. MAOB had the highest binding affinity with amitriptyline, followed by SLC6A4 and DRD2. Binding stability was enhanced by salt bridges and \u03c0\u2010stacking interactions. Mirtazapine formed strong binding affinities with HTR2C, SLC6A4, and CHRNA4 through hydrogen bonds and \u03c0\u2010stacking interactions. Escitalopram exhibited the highest affinity for SLC6A3, followed by HTR2C.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>All three drugs regulated serotonin, norepinephrine (NE), and dopamine, but target specificity, pathways, and binding patterns differed. Amitriptyline exhibited stronger antidepressant effects and broader mechanisms but a higher risk of side effects. Mirtazapine\u2019s dual mechanism regulates broad targets with reliable efficacy and fewer side effects. Escitalopram selectively acts on serotonin\u2010related targets, with narrow actions and potentially fewer side effects. These findings align with the clinical profiles of the antidepressant efficacy and side effects.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1155\/da\/6981320","type":"journal-article","created":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T06:02:42Z","timestamp":1791007362000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparative Analysis of Antidepressant Mechanisms and Side Effects: Network Pharmacology and Molecular Docking Study of Amitriptyline, Mirtazapine, and Escitalopram for Treating Major Depressive Disorder"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3793-550X","authenticated-orcid":false,"given":"Chuanjun","family":"Zhuo","sequence":"first","affiliation":[{"name":"Laboratory of Computational and Computational Psychiatry (CBCP_Lab) Tianjin Anding Hospital Mental Health Center of Tianjin Medical University  Tianjin 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