Graphical AbstractVerifiedDrug Target Identification and Drug Repurposing in Lung Cancer via Computational Drug-Drug Interaction Analysis
Lung cancer remains a leading cause of cancer-related mortality worldwide. Despite advances in targeted therapies and immunotherapies, drug resistance and adverse effects necessitate novel therapeutic strategies. This study employs a computational approach integrating drug-target interaction networks, gene expression profiles, and drug-drug interaction data to identify potential drug targets and repurpose existing drugs for lung cancer treatment. We analyzed transcriptomic data from lung cancer patients and constructed a protein-protein interaction network to pinpoint hub genes. Subsequently, we screened FDA-approved drugs against these targets using molecular docking and drug repurposing databases. Our analysis identified several promising candidates, including [Drug A] and [Drug B], which exhibited high binding affinities and favorable pharmacokinetic profiles. In vitro validation in lung cancer cell lines confirmed the anti-proliferative effects of these drugs. These findings provide a foundation for clinical trials and highlight the utility of computational drug repurposing in oncology.
