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Implementation of a fluorescence-based screening assay identifies histamine H3 receptor antagonists clobenpropit and iodophenpropit as subunit-selective N-methyl-D-aspartate receptor antagonists.

ABSTRACT: N-Methyl-D-aspartate (NMDA) receptors are ligand-gated ion channels that mediate a slow, Ca(2+)-permeable component of excitatory synaptic transmission in the central nervous system and play a pivotal role in synaptic plasticity, neuronal development, and several neurological diseases. We describe a fluorescence-based assay that measures NMDA receptor-mediated changes in intracellular calcium in a BHK-21 cell line stably expressing NMDA receptor NR2D with NR1 under the control of a tetracycline-inducible promoter (Tet-On). The assay selectively identifies allosteric modulators by using supramaximal concentrations of glutamate and glycine to minimize detection of competitive antagonists. The assay is validated by successfully identifying known noncompetitive, but not competitive NMDA receptor antagonists among 1800 screened compounds from two small focused libraries, including the commercially available library of pharmacologically active compounds. Hits from the primary screen are validated through a secondary screen that used two-electrode voltage-clamp recordings on recombinant NMDA receptors expressed in Xenopus laevis oocytes. This strategy identified several novel modulators of NMDA receptor function, including the histamine H3 receptor antagonists clobenpropit and iodophenpropit, as well as the vanilloid receptor transient receptor potential cation channel, subfamily V, member 1 (TRPV1) antagonist capsazepine. These compounds are noncompetitive antagonists and the histamine H3 receptor ligand showed submicromolar potency at NR1/NR2B NMDA receptors, which raises the possibility that compounds can be developed that act with high potency on both glutamate and histamine receptor systems simultaneously. Furthermore, it is possible that some actions attributed to histamine H3 receptor inhibition in vivo may also involve NMDA receptor antagonism.

SUBMITTER: Hansen KB

PROVIDER: S-EPMC2879924 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Implementation of a fluorescence-based screening assay identifies histamine H3 receptor antagonists clobenpropit and iodophenpropit as subunit-selective N-methyl-D-aspartate receptor antagonists.

Hansen Kasper B KB Mullasseril Praseeda P Dawit Sara S Kurtkaya Natalie L NL Yuan Hongjie H Vance Katie M KM Orr Anna G AG Kvist Trine T Ogden Kevin K KK Le Phuong P Vellano Kimberly M KM Lewis Iestyn I Kurtkaya Serdar S Du Yuhong Y Qui Min M Murphy T J TJ Snyder James P JP Bräuner-Osborne Hans H Traynelis Stephen F SF

The Journal of pharmacology and experimental therapeutics 20100302 3

N-Methyl-D-aspartate (NMDA) receptors are ligand-gated ion channels that mediate a slow, Ca(2+)-permeable component of excitatory synaptic transmission in the central nervous system and play a pivotal role in synaptic plasticity, neuronal development, and several neurological diseases. We describe a fluorescence-based assay that measures NMDA receptor-mediated changes in intracellular calcium in a BHK-21 cell line stably expressing NMDA receptor NR2D with NR1 under the control of a tetracycline- ...[more]

PMID: 20197375

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Project description:Histamine receptors (HRs) are excellent drug targets for the treatment of diseases, such as schizophrenia, psychosis, depression, migraine, allergies, asthma, ulcers, and hypertension. Among them, the human H(3) histamine receptor (hH(3)HR) antagonists have been proposed for specific therapeutic applications, including treatment of Alzheimer's disease, attention deficit hyperactivity disorder (ADHD), epilepsy, and obesity. However, many of these drug candidates cause undesired side effects through the cross-reactivity with other histamine receptor subtypes. In order to develop improved selectivity and activity for such treatments, it would be useful to have the three-dimensional structures for all four HRs. We report here the predicted structures of four HR subtypes (H(1), H(2), H(3), and H(4)) using the GEnSeMBLE (GPCR ensemble of structures in membrane bilayer environment) Monte Carlo protocol, sampling ∼35 million combinations of helix packings to predict the 10 most stable packings for each of the four subtypes. Then we used these 10 best protein structures with the DarwinDock Monte Carlo protocol to sample ∼50 000 × 10(20) poses to predict the optimum ligand-protein structures for various agonists and antagonists. We find that E206(5.46) contributes most in binding H(3) selective agonists (5, 6, 7) in agreement with experimental mutation studies. We also find that conserved E5.46/S5.43 in both of hH(3)HR and hH(4)HR are involved in H(3)/ H(4) subtype selectivity. In addition, we find that M378(6.55) in hH(3)HR provides additional hydrophobic interactions different from hH(4)HR (the corresponding amino acid of T323(6.55) in hH(4)HR) to provide additional subtype bias. From these studies, we developed a pharmacophore model based on our predictions for known hH(3)HR selective antagonists in clinical study [ABT-239 1, GSK-189,254 2, PF-3654746 3, and BF2.649 (tiprolisant) 4] that suggests critical selectivity directing elements are: the basic proton interacting with D114(3.32), the spacer, the aromatic ring substituted with the hydrophilic or lipophilic groups interacting with lipophilic pockets in transmembranes (TMs) 3-5-6 and the aliphatic ring located in TMs 2-3-7. These 3D structures for all four HRs should help guide the rational design of novel drugs for the subtype selective antagonists and agonists with reduced side effects.

Dataset Information

Implementation of a fluorescence-based screening assay identifies histamine H3 receptor antagonists clobenpropit and iodophenpropit as subunit-selective N-methyl-D-aspartate receptor antagonists.

Publications

Implementation of a fluorescence-based screening assay identifies histamine H3 receptor antagonists clobenpropit and iodophenpropit as subunit-selective N-methyl-D-aspartate receptor antagonists.

Similar Datasets

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