Identification of potent HDAC 2 inhibitors using E-pharmacophore modelling, structure-based virtual screening and molecular dynamic simulation

Author:

Pai Padmini,Kumar Avinash,Shetty Manasa Gangadhar,Kini Suvarna Ganesh,Krishna Manoj Bhat,Satyamoorthy Kapaettu,Babitha Kampa SundaraORCID

Abstract

Abstract Histone deacetylase 2 (HDAC 2) of class I HDACs plays a major role in embryonic and neural developments. However, HDAC 2 overexpression triggers cell proliferation by diverse mechanisms in cancer. Over the decades, many pan and class-specific inhibitors of HDAC were discovered. Limitations such as toxicity and differential cell localization of each isoform led researchers to hypothesize that isoform selective inhibitors may be relevant to bring about desired effects. In this study, we have employed the PHASE module to develop an e-pharmacophore model and virtually screened four focused libraries of around 300,000 compounds to identify isoform selective HDAC 2 inhibitors. The compounds with phase fitness score greater than or equal to 2.4 were subjected to structure-based virtual screening with HDAC 2. Ten molecules with docking score greater than  -12 kcal/mol were chosen for selectivity study, QikProp module (ADME prediction) and dG/bind energy identification. Compound 1A with the best dock score of  -13.3 kcal/mol and compound 1I with highest free binding energy,  -70.93 kcal/mol, were selected for molecular dynamic simulation studies (40 ns simulation). The results indicated that compound 1I may be a potent and selective HDAC 2 inhibitor. Further, in vitro and in vivo studies are necessary to validate the potency of selected lead molecule and its derivatives. Graphical abstract

Funder

department of biotechnology, ministry of science and technology

Manipal Academy of Higher Education, Manipal

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Catalysis

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