Synergism of virtual screening and medicinal chemistry: Identification and optimization of allosteric antagonists of metabotropic glutamate receptor 1

• Published in: Bioorganic & medicinal chemistry Vol. 17; no. 15; pp. 5708 - 5715
• Main Authors: Noeske, Tobias, Trifanova, Dina, Kauss, Valerjans, Renner, Steffen, Parsons, Christopher G., Schneider, Gisbert, Weil, Tanja
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01-08-2009; Elsevier
• Subjects: Allosteric Regulation; Animals; Antagonist; Binding Sites; Biological and medical sciences; Drug Discovery; Glutamatergic system (aspartate and other excitatory aminoacids); Ligands; Medical sciences; Metabotropic; mGluR1; Models, Molecular; Neuropharmacology; Neurotransmitters. Neurotransmission. Receptors; Pharmacology. Drug treatments; Protein Binding; Rats; Rats, Sprague-Dawley; Receptors, Metabotropic Glutamate - antagonists & inhibitors; Receptors, Metabotropic Glutamate - chemistry; Receptors, Metabotropic Glutamate - metabolism; Self-organizing map; Small Molecule Libraries - chemical synthesis; Small Molecule Libraries - chemistry; Small Molecule Libraries - pharmacology; Structure-Activity Relationship; Virtual screening; Virtual screening; mGluR1; Metabotropic; Antagonist; Self-organizing map; Group I mglu glutamate receptor; Cyclopropane derivatives; mglu1 glutamate receptor; Glutamate receptor; Selectivity; Neural network; Morpholine derivatives; Ketone; In vitro; Optimization; Pyridine derivatives; Self-organising feature maps; Structure activity relation; Metabotropic receptor; Learning algorithm
• ISSN: 0968-0896; 1464-3391
• DOI: 10.1016/j.bmc.2009.05.072

We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by
virtual screening and subsequent hit optimization.
We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by
virtual screening and subsequent hit optimization. For ligand-based
virtual screening, molecules were represented by a topological pharmacophore descriptor (CATS-2D) and clustered by a self-organizing map (SOM). The most promising compounds were tested in mGluR1 functional and binding assays. We identified a potent chemotype exhibiting selective antagonistic activity at mGluR1 (functional IC
50
=
0.74
±
0.29
μM). Hit optimization yielded lead structure
16 with an affinity of
K
i
=
0.024
±
0.001
μM and greater than 1000-fold selectivity for mGluR1 versus mGluR5. Homology-based receptor modelling suggests a binding site compatible with previously reported mutation studies. Our study demonstrates the usefulness of ligand-based
virtual screening for scaffold-hopping and rapid lead structure identification in early drug discovery projects.