Integrated QSAR, molecular docking, and dynamics-based discovery of a potent selective HDAC1 inhibitor with therapeutic potential in aggressive cancers.

This research introduces a comprehensive computational and experimental approach aimed at the systematic design of selective Histone Deacetylase 1 (HDAC1) inhibitors, which hold therapeutic promise for treating aggressive cancers. A comprehensive Quantitative Structure-Activity Relationship (QSAR) model was constructed utilizing 1168 experimentally validated HDAC1 inhibitors, incorporating molecular descriptors associated with hydrogen bonding, steric, and electronic properties. The validated model, with a R of 0.80 and a Q of 0.80, was utilized for the virtual screening of the ChemDiv HDAC library, successfully identifying high-potential hits. The leading compounds underwent receptor-based molecular docking with the HDAC1 crystal structure (PDB ID: 4BKX), which highlighted essential interactions such as zinc ion coordination and π-π stacking. Notably, compound 0356-0096 demonstrated a higher binding affinity than the reference inhibitor vorinostat. Molecular dynamics (MD) simulations conducted over a duration of 500 ns demonstrated the stability of the complex and a decrease in flexibility, as evidenced by analyses of Root Mean Square Deviation (RMSD) and Fluctuation (RMSF). The analysis of simulation trajectories through Principal Component Analysis (PCA) and the mapping of the Free Energy Landscape (FEL) revealed stable low-energy conformations that align with thermodynamically favorable binding conditions. The results of ADMET profiling demonstrated that the lead compounds exhibit good oral bioavailability, low toxicity, and favorable metabolic stability. Validation through in vitro methods using the MTT assay on MDA-MB-231 (triple-negative breast cancer) and A431 (epidermoid carcinoma) cell lines revealed significant, dose-dependent cytotoxic effects, with IC values of 2.7 μM and 91.6 nM, respectively. The computed Selectivity Index (SI) demonstrated a preferential cytotoxic effect on cancer cells in comparison to normal NRK kidney cells. This integrative QSAR-docking-MD-FEL-MTT approach effectively identified compound 0356-0096 as a potent and selective HDAC1 inhibitor. By combining predictive computational models with empirical validation, it provides a structured pathway for the preclinical development of targeted epigenetic cancer therapeutics.