­­­­Computational Identification of Taxus baccata-Derived Phytochemicals Targeting EZH2 to Overcome Therapeutic Resistance in Melanoma

Abstract Therapy resistance remains a significant challenge in melanoma treatment, despite recent advances in targeted therapies and immunotherapies. Enhancer of zeste homolog 2 (EZH2) has been identified as a critical target for overcoming resistance. However, the availability of effective inhibitors remains limited, emphasizing the need for novel therapeutic strategies to address this issue. This study aimed to identify potential EZH2 inhibitors derived from Taxus baccata using computational methods to overcome melanoma therapy resistance. A total of 98 phytochemical compounds from Taxus baccata were selected for in silico screening. The compounds were assessed using molecular docking to predict their binding affinities with EZH2. The pharmacokinetic properties of the compounds were evaluated using ADMET analysis, and Density Functional Theory (DFT) was used to assess their electronic properties. The top compounds were subjected to 100 ns molecular dynamics (MD) simulations to examine their stability and interaction dynamics, using tazemetostat and GSK-126 as reference inhibitors. Among the screened compounds, sotetsuflavone, ginkgetin, amentoflavone, and podocarpusflavone A were identified as potential EZH2 inhibitors. amentoflavone exhibited the highest binding affinity, strong interaction stability, and favorable pharmacokinetic profile. It also demonstrated the lowest negative binding free energy (MMPBSA), indicating a superior binding strength. These findings suggest that amentoflavone is the most promising candidate for further development, with the other compounds providing valuable scaffolds for optimization. This study provides a computational basis for designing novel EZH2 inhibitors from Taxus baccata . Further experimental validation is required to confirm these findings and explore the potential therapeutic applications of these phytochemicals in clinical settings.