Pharmacophore-based virtual screening of ZINC database, molecular modeling and designing new derivatives as potential HDAC6 inhibitors.

To date, many HDAC6 inhibitors have been identified and developed but none is clinically approved as of now. Through this study, we aim to obtain novel HDAC6 selective inhibitors and provide new insights into the detailed structural design of potential HDAC6 inhibitors. A HypoGen-based 3D QSAR HDAC6 pharmacophore was built and used as a query model to screen approximately 8 million ZINC database compounds. First, the ZINC Database was filtered using ADMET, followed by pharmacophore-based library screening. Using fit value and estimated activity cutoffs, a final set of 54 ZINC hits was obtained that were further investigated using molecular docking with the crystal structure of human histone deacetylase 6 catalytic domain 2 in complex with Trichostatin A (PDB ID: 5EDU). Through detailed in silico screening of the ZINC database, we shortlisted three hits as the lead molecules for designing novel HDAC6 inhibitors with better efficacy. Docking with 5EDU, followed by ADMET and TOPKAT analysis of modified ZINC hits provided 9 novel potential HDAC6 inhibitors that possess better docking scores and 2D interactions as compared to the control ZINC hit molecules. Finally, a 50 ns MD analysis run followed by Protein-Ligand Interaction Energy (PLIE) analysis of the top scored hits provided a novel molecule N1 that showed promisingly similar results to that of Ricolinostat (a known HDAC6 inhibitor). The comparable result of the designed hits to established HDAC6 inhibitors suggests that these compounds might prove to be successful HDAC6 inhibitors in future. Designed novel hits that might act as good HDAC6 inhibitors derived from ZINC database using combined molecular docking and modeling approaches.