Abstract
In the pursuit of advancing precision therapy for lung cancer, this study explores the repositioning potential of a FDA approved methotrexate derivative, with a specific focus on its interaction with the Dihydrofolate Reductase (DHFR) enzyme. Leveraging transcriptomic insights and structural integration, our research employs a multifaceted approach, encompassing drug-drug similarity analysis and cavity-guided blind docking. The investigation commences with the identification of transcriptomic profiles closely resembling established lung cancer therapeutics, revealing a subset of compounds, including the methotrexate derivative, exhibiting high similarity. Subsequent to the structural refinement of the DHFR enzyme through meticulous preprocessing, our study unveils alterations that enhance the accuracy of the protein model, establishing a reliable foundation for further analyses. The application of cavity detection techniques on DHFR exposes potential binding sites crucial for enzyme activity. Employing blind docking strategies, we elucidate the interaction patterns and binding affinities of the methotrexate derivative within these identified cavities. The results highlight the potential of the studied compound, shedding light on its role as a promising candidate for precision therapy in lung cancer through targeted modulation of the DHFR enzyme. This integrative approach, combining transcriptomic insights and structural analyses, contributes valuable knowledge to the repositioning of FDA-approved methotrexate derivatives for enhanced therapeutic efficacy in lung cancer treatment.
Keywords: Lung cancer, methotrexate, Transcriptomic similarity, Repurposing and docking