Pharmaceutical and personal care products (PPCPs), as ubiquitous emerging contaminants, present undercharacterized neuropsychiatric hazards through environmental exposure. This investigation employs convergent multi-omics strategies - integrating toxicogenomic discovery, disease-associated genomic mapping, and transcriptomic profiling - to elucidate mechanistic linkages between PPCPs bioactivity and depressive pathogenesis. Through systematic analysis of Nanjing's aquatic chemical burden (prioritizing dimenhydrinate, ibuprofen, padimate-O, caffeine, and roxithromycin), we identified 3073 conserved molecular targets bridging PPCPs toxicity and depression etiology via Comparative Toxicogenomics Database and GeneCards interrogation. Functional ontology revealed dysregulated pathways encompassing lipidomic remodeling, IL-17-mediated neuroinflammation, and synaptic transmission deficits. Ensembled machine learning algorithms (Lasso regression, XGBoost, random forest) converged on seven high-fidelity candidate biomarkers (HSPA8, CBX1, CD59, CHAF1A, CUX1, ID2, RPL3) demonstrating stress-adaptive, chromatin regulatory, and immunomodulatory functions. Molecular docking predicted strong binding affinities between PPCPs and depression-related proteins, notably dimenhydrinate with CHAF1A (- 6.1 kcal/mol) and HSPA8 (- 6.1 kcal/mol), suggesting multi-target modulation. This work proposes a computational framework to map molecular interactions between specific PPCPs and depression-associated pathways. Candidate targets highlight testable hypotheses for future experimental validation. These findings suggest selected PPCPs with neuroactive properties may warrant further investigation as environmental modifiers of depression risk.