Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays

• Published in: PloS one 2015-10, Vol.10 (10), p.e0139588
• Main Authors: Noor, Zainab, Afzal, Noreen, Rashid, Sajid
• Format: Article
• Language: English
• Subjects: Analysis; Binding Sites; Bioinformatics; Biological activity; Cancer; Cell cycle; Cell survival; Chemical properties; Chromatin; Computer simulation; Deoxyribonucleic acid; Deregulation; DNA; Epigenetic inheritance; Gene expression; HDAC2 protein; Health aspects; Histone deacetylase; Histone Deacetylase Inhibitors - chemistry; Histone Deacetylase Inhibitors - pharmacology; Hydrogen; Hydrogen atoms; Hydrogen-based energy; Inhibitors; Inhibitory Concentration 50; Isoenzymes - antagonists & inhibitors; Isoforms; Lead compounds; Ligands; Medical screening; Modelling; Molecular dynamics; Molecular Dynamics Simulation; Pharmacology; Quantitative Structure-Activity Relationship; Structure-activity relationships; Therapy; Transformed cells; Two dimensional models
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0139588

Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC50 values and experimental energy scores with extensive validations. The QSAR model having an external R2 value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy.