Structure-Based Virtual Screening to Identify Negative Allosteric Modulators of NMDA.

Abstract

Background: NMDA (N-methyl-D-aspartate) receptor is one of the ionotropic receptor subtypes of glutamate, the most abundant excitatory neurotransmitter in the human brain. Besides physiological roles in learning and memory, neuronal plasticity and somatosensory function NMDAR overstimulation are also implicated in a pathophysiological mechanism of 'excitotoxicity.' In this study, an allosteric site has been focused on to design inhibitors of the most abundant form of this receptor of utility in many acute (stroke, traumatic brain injury) and chronic neurodegenerative diseases such as Parkinson's disease, Huntington's, Alzheimer's, and others.

Methods: In order to target this specific site at the interdimer interface of the ligand-binding domain of GluN2A-containing NMDA-Rs, blood-brain barrier-permeable potentially therapeutic compounds, as opposed to only pharmacological tools currently available, were sought. Pharmacophorebased virtual screening, docking, computational ADME prediction techniques, and MD simulation studies were used.

Results: Proceeding through the in-silico methodology, the study was successful at reaching 5 compounds from ChEMBL Database, which were predicted to be potential NMDA inhibitor drugs.

Conclusion: The products of the study are compounds that have been validated through pharmacophore and score-based screening and MD simulation techniques to be allosterically inhibiting NMDA receptors and with favorable pharmacokinetic profiles. They are likely to be therapeutic agents ready for in-vitro and in-vivo testing.