Pharmacophore-based virtual screening for identification of potential selective inhibitors of human histone deacetylase 6

Authors: Uba AI, Yelekçi K
Publication: Comput Biol Chem
Software: ADMET Predictor®


Histone deacetylase (HDAC) 6 plays a role in oncogenic transformation and cancer metastasis via tubulin deacetylation, making it a critical target for anticancer drug design. However, lack of selectivity shown by many of the current HDAC6 inhibitors in clinical use and trials prompts the continuous search for selective inhibitors. Here, 10 pharmacophore hypotheses were developed based on the 3D common features of training set of 20 HDAC inhibitors in clinical use and trials. The hypotheses were validated using a test set of another 20 HDAC inhibitors along with 400 inactive (decoys) molecules based on Güner-Henry pharmacophore scoring method. Hypothesis 1 consisting of 1 H-bond donor, 1 H-bond acceptor and 2 hydrophobic features, was used to screen “DruglikeDiverse” database using Biovia Discovery Studio 4.5. The top 10 hit compounds were selected based on the pharmacophore fit values (>3.00). Their binding affinity against HDAC6 compared to class I HDACs (1, 2, 3 & 8) and a class IIa member (HDAC7), was calculated by molecular docking using AutoDock4. The stability of binding modes of 2 potential HDAC6-selective inhibitors (ENA501965 and IBS399024) was examined by 30 ns-molecular dynamics (MD) simulation using nanoscale MD (NAMD) software. Both ligands showed potential stability in HDAC6 active site over time. Therefore, these may provide additional scaffolds for further optimization towards the design of safe, potent and selective HDAC6 inhibitors.