Pharmacophore modeling, 3D-QSAR, and MD simulation-based overture for the discovery of new potential HDAC1 inhibitors.

Histone deacetylases (HDACs) are important epigenetic regulators that modulate the activity of histone and non-histone proteins leading to various cancers. Histone deacetylase 1 (HDAC1) is a member of class 1 HDAC family related to different cancers. However, the nonselective profile of existing HDAC1 inhibitors restricted their clinical utility. Therefore, the identification of new HDAC1 selective inhibitors may be fruitful against cancer therapy. In this present work, a pharmacophore model was built using 60 benzamide-based known HDAC1 selective inhibitors and it was used further to filter the large epigenetic molecular database of small molecules. Further, the 3D-QSAR model was built using the best common pharmacophore hypothesis consisting of higher PLS statistics of R² of 0.89, Q² of 0.83, variance ratio (F) of 65.7 and Pearson-r value of 0.94 revealing the model reliability and its high predictive power. The screened hits of the pharmacophore model were then subjected to molecular docking against HDAC1 to identify high-affinity lead molecules. The top 10 hits were ranked from the docking studies using docking scores for lead optimization. The potential hit molecules M1 and M2 identified from the study showed promising interaction during HDAC1 docking and MD simulation studies with acceptable ADME properties. Also, the newly designed lead compounds M11 and M12 may be considered highly potential inhibitors against HDAC1. The 3D-QSAR analysis, conformational requirements, and observations noticed in the MD simulations study will enable the optimization of lead molecules and to design of novel effective, and selective HDAC1 inhibitors in the future.