Designing potential HDAC3 inhibitors to improve memory and learning

Abstract

The work presented here explores the structural and physicochemical features important for benzamide-based HDAC3 inhibitors to get an idea about the design aspect of potential inhibitors. A number of molecular modeling studies (3D-QSAR CoMFA and CoMSIA, Bayesian classification modeling) were performed on 113 diverse set of benzamide-based HDAC3 inhibitors. All these models developed are statistically reliable and correlate the SAR observations. Electron withdrawing substitution is favorable but the bulky hydrophobic group at the cap region reduces HDAC3 inhibition. Hydrophobicity and steric feature of the aryl linker function favor the activity. Aryl group substituted benzamide functionality is not favorable for HDAC3 inhibition. The amide function of the benzamide moiety is essential for Zn²⁺ chelation and the carboxylic acid function may serve as a hydrogen bond acceptor (HBA) feature. Moreover, electron withdrawing substituent at the benzamide moiety influences activity whereas steric and hydrophobic substituents reduce HDAC3 inhibition. Overall, this study may provide a valuable insight on the design of better active HDAC3 inhibitors in future.

Communicated by Ramaswamy H. Sarma

Keywords:

• HDAC3 inhibitor
• memory and learning
• QSAR
• Bayesian model
• CoMFA
• CoMSIA

Acknowledgments

Authors are thankful to the authority of Jadavpur University, Kolkata, India and BITS-Pilani, Hyderabad Campus, Shamirpet, Hyderabad, India for providing research facilities.

Disclosure statement

Authors declare no conflict of interests.