Hexonic derivatives as human GABA-AT inhibitors: A molecular docking approach

Dharmaraj Senthilkumar,Sivaraman Jayanthi,Anbarasu Kannan

doi:10.3329/bjp.v10i1.20642

Abstract

Human γ-aminobutyric acid aminotransferase (GABA-AT), a pyridoxal phosphate dependent enzyme is responsible for the degradation of the inhibitory neurotransmitter GABA. Currently, GABA-AT is a potential drug target for epilepsy due to the selective inhibition in brain. In this computational study, we mainly focus on screening of novel lead candidates against GABA-AT using hexonic derivatives. Structure based virtual screening is performed in Vina that screened top hits based on least binding affinity. Further re-docking on hits is performed in AutoDock results in identification of leads with favorable binding energy and hydrogen bond interactions confirmed the effective inhibition. In conclusion, leads 3-aminohex-5-enoic acid and AG-E-60842 can acts as specific leads for GABA-AT and assist in discovery of novel anti-epileptic drugs.

Highlights

In mammalian central nervous system, -aminobutyric acid (GABA) is a predominant inhibitory neurotransmitter that involved in modulation of central inhibitory tone via activation of various receptors like GABAA, GABAC (Osolodkin et al, 2009; Smith and Simpson, 2003)
Hit identification by virtual screening: For hit identification, structure-based virtual screening was performed in Vina software (Trott, Olson 2010) with hexonic derivatives targeting active sites of GABA-AT
We carried out homology modeling of human GABA-AT for inbuilt structure for inhibitor design

Summary

Introduction

In mammalian central nervous system, -aminobutyric acid (GABA) is a predominant inhibitory neurotransmitter that involved in modulation of central inhibitory tone via activation of various receptors like GABAA, GABAC (Osolodkin et al, 2009; Smith and Simpson, 2003). Ligand preparation: Twelve hexonic acid derivatives were selected as ligand dataset for inhibitor design. Hit identification by virtual screening: For hit identification, structure-based virtual screening was performed in Vina software (Trott, Olson 2010) with hexonic derivatives targeting active sites of GABA-AT.

Results

Conclusion