Identifying potential core genes for chronic obstructive pulmonary disease associated with cocaine exposure via integrated bioinformatics and network toxicology.

Cocaine abuse can damage various organ systems; however, the molecular mechanisms underlying its potential contribute to chronic obstructive pulmonary disease (COPD) remain poorly understood. In this study, an integrative computational framework was used to investigate the molecular links between cocaine exposure and COPD and to identify potential key targets and regulatory mechanisms. Cocaine‑associated targets and COPD‑related differentially expressed genes (DEGs) were collected from public databases and transcriptomic datasets, yielding 34 overlapping DEGs that may be associated with both cocaine exposure and COPD. Functional enrichment and protein-protein interaction network analyses indicated that DEGs were mainly involved in cancer-, inflammation-, and virus-related pathways. Three machine learning algorithms combined with network topology analysis identified cathepsin D (CTSD) as a core target associated with multiple immune cell types. Single-cell RNA sequencing analysis further showed that CTSD is highly expressed in macrophages. Virtual knockout analysis using scTenifoldKnk identified 113 consistently responsive genes, which were functionally enriched in autoimmune reactions, infection-induced immune activation, and antigen presentation pathways. Molecular docking and molecular dynamics simulations demonstrated strong binding affinity and stable interactions between cocaine and CTSD, supporting a potential mechanistic role in COPD related to cocaine exposure. Additionally, ten CTSD-associated drugs were identified from DSigDB and evaluated using molecular docking, pharmacokinetic analysis, and druglikeness assessment. Collectively, this study highlights CTSD as a candidate molecular target linking cocaine exposure to COPD and provides a theoretical basis for future experimental and toxicological investigations.