%0 Journal Article %A Singh, Ravi %A Ganeshpurkar, Ankit %A Kumar, Devendra %A Kumar, Dileep %A Kumar, Ashok %A Kumar Singh, Sushil %D 2019 %T Identifying potential GluN2B subunit containing N-Methyl-D-aspartate receptor inhibitors: an integrative in silico and molecular modeling approach %U https://tandf.figshare.com/articles/journal_contribution/Identifying_potential_GluN2B_subunit_containing_N-Methyl-D-aspartate_receptor_inhibitors_an_integrative_i_in_silico_i_and_molecular_modeling_approach/8668085 %R 10.6084/m9.figshare.8668085.v1 %2 https://tandf.figshare.com/ndownloader/files/15959084 %K NMDAR %K GluN2B %K Pharmit %K Amber %X

N-methyl-D-aspartate receptors (NMDARs), a class of ligand-gated ion channels, are involved in non-selective cation transport across the membrane. These are contained in glutamatergic synapse and produce excitatory effects leading to synaptic plasticity and memory function. GluN1-GluN2B, a subtype of NMDAR(s), has significant role in neurodegeneration, amyloid β (Aβ) induced synaptic dysfunction and loss. Thus, targeting and inhibiting GluN1-GluN2B may be effective in the management of neurodegenerative diseases including Alzheimer’s disease. In the present study, ligand and structure-based approaches were tried to identify the inhibitors. The pharmacophore, developed from co-crystallised ifenprodil, afforded virtual hits, which were further subjected through drug likeliness and PAINS filters to remove interfering compounds. Further comprehensive docking studies, free energy calculations and ADMET studies resulted in two virtual leads. The leads, ZINC257261614 and ZINC95977857 displayed good docking scores of −12.90 and −12.20 Kcal/mol and free binding energies of −60.83 and −61.83 Kcal/mol, respectively. The compounds were having acceptable predicted ADMET profiles and were subjected to molecular dynamic (MD) studies. The MD simulation produced stable complexes of these ligands with GluN1-GluN2B subunit having protein and ligand RMSD in acceptable limit. AbbreviationsAD

Alzheimer's disease

ADME

Absorption distribution metabolism and excretion

ATD

Amino terminal domain

BBB

Blood-brain barrier

CNS

Central nervous system

CREB

cAMP response element binding protein

CTD

Carboxy-terminal domain

Glu

Glutamate

GMQE

Global model quality estimation

HTVS

High throughput virtual screening

HIA

Human intestinal absorption

LGA

Lamarckian genetic algorithm

MD

Molecular dynamics

MM-GBSA

Molecular mechanics, the Generalised Born model for Solvent Accessibility

NMDAR

N-methyl-D-aspartate receptors

PAINS

Pan assay interference compounds

RMSD

Root-mean square deviation

RMSF

Root-mean-square fluctuation

SMARTS

SMILES arbitrary target specification

SP

standard precision

XP

extra precision

Alzheimer's disease

Absorption distribution metabolism and excretion

Amino terminal domain

Blood-brain barrier

Central nervous system

cAMP response element binding protein

Carboxy-terminal domain

Glutamate

Global model quality estimation

High throughput virtual screening

Human intestinal absorption

Lamarckian genetic algorithm

Molecular dynamics

Molecular mechanics, the Generalised Born model for Solvent Accessibility

N-methyl-D-aspartate receptors

Pan assay interference compounds

Root-mean square deviation

Root-mean-square fluctuation

SMILES arbitrary target specification

standard precision

extra precision

Communicated by Ramaswamy H. Sarma

%I Taylor & Francis