Exploring the overlapping binding sites of ifenprodil and EVT-101 in GluN2B-containing NMDA receptors using novel chicken embryo forebrain cultures and molecular modeling.

N-methyl-d-aspartate receptors (NMDAR) are widely expressed in the brain. GluN2B subunit-containing NMDARs has recently attracted significant attention as potential pharmacological targets, with emphasis on the functional properties of allosteric antagonists. We used primary cultures from chicken embryo forebrain (E10), expressing native GluN2B-containing NMDA receptors as a novel model system. Comparing the inhibition of calcium influx by well-known GluN2B subunit-specific allosteric antagonists, the following rank order of potency was found: EVT-101 (EC 50 22 ± 8 nmol/L) > Ro 25-6981 (EC 50 60 ± 30 nmol/L) > ifenprodil (EC 50 100 ± 40 nmol/L) > eliprodil (EC 50 1300 ± 700 nmol/L), similar to previous observations in rat cortical cultures and cell lines overexpressing chimeric receptors. The less explored Ro 04-5595 had an EC 50 of 186 ± 32 nmol/L. Venturing to explain the differences in potency, binding properties were further studied by in silico docking and molecular dynamics simulations using x-ray crystal structures of GluN1/GluN2B amino terminal domain. We found that Ro 04-5595 was predicted to bind the recently discovered EVT-101 binding site, not the ifenprodil-binding site. The EVT-101 binding pocket appears to accommodate more structurally different ligands than the ifenprodil-binding site, and contains residues essential in ligand interactions necessary for calcium influx inhibition. For the ifenprodil site, the less effective antagonist (eliprodil) fails to interact with key residues, while in the EVT-101 pocket, difference in potency might be explained by differences in ligand-receptor interaction patterns.

In Silico Methods for the Discovery of Orthosteric GABAB Receptor Compounds.

The GABAB receptor (GABAB-R) is a heterodimeric class C G protein-coupled receptor comprised of the GABAB1a/b and GABAB2 subunits. The endogenous orthosteric agonist γ-amino-butyric acid (GABA) binds within the extracellular Venus flytrap (VFT) domain of the GABAB1a/b subunit. The receptor is associated with numerous neurological and neuropsychiatric disorders including learning and memory deficits, depression and anxiety, addiction and epilepsy, and is an interesting target for new drug development. Ligand- and structure-based virtual screening (VS) are used to identify hits in preclinical drug discovery. In the present study, we have evaluated classical ligand-based in silico methods, fingerprinting and pharmacophore mapping and structure-based in silico methods, structure-based pharmacophores, docking and scoring, and linear interaction approximation (LIA) for their aptitude to identify orthosteric GABAB-R compounds. Our results show that the limited number of active compounds and their high structural similarity complicate the use of ligand-based methods. However, by combining ligand-based methods with different structure-based methods active compounds were identified in front of DUDE-E decoys and the number of false positives was reduced, indicating that novel orthosteric GABAB-R compounds may be identified by a combination of ligand-based and structure-based in silico methods.