Evaluation of allosteric NMDA receptor modulation by GluN2A-selective antagonists using pharmacological equilibrium modeling.

NMDA-type ionotropic glutamate receptors are critically involved in excitatory neurotransmission and their dysfunction is implicated in many brain disorders. Allosteric modulators with selectivity for specific NMDA receptor subtypes are therefore attractive as therapeutic agents, and sustained drug discovery efforts have resulted in a wide range of new allosteric modulators. However, evaluation of allosteric NMDA receptor modulators is limited by the lack of operational ligand-receptor models to describe modulator binding dissociation constants (K) and effects on agonist binding affinity (α) and efficacy (β).

Modulating inhibitory response control through potentiation of GluN2D subunit-containing NMDA receptors.

NMDA receptors containing GluN2D subunits are expressed in the subthalamic nucleus and external globus pallidus, key nuclei of the indirect and hyperdirect pathways of the basal ganglia. This circuitry integrates cortical input with dopaminergic signaling to select advantageous behaviors among available choices. In the experiments described here, we characterized the effects of PTC-174, a novel positive allosteric modulator (PAM) of GluN2D subunit-containing NMDA receptors, on response control regulated by this circuitry.

PTC-174, a positive allosteric modulator of NMDA receptors containing GluN2C or GluN2D subunits.

NMDA receptors are ionotropic glutamate receptors that mediate excitatory neurotransmission. The diverse functions of these receptors are tuned by deploying different combinations of GluN1 and GluN2 subunits (GluN2A-D) to form either diheteromeric NMDA receptors, which contain two GluN1 and two identical GluN2 subunits, or triheteromeric NMDA receptors, which contain two GluN1 and two distinct GluN2 subunits. Here, we characterize PTC-174, a novel positive allosteric modulator (PAM) of receptors containing GluN2C or GluN2D subunits.

Structural Basis for Negative Allosteric Modulation of GluN2A-Containing NMDA Receptors.

NMDA receptors mediate excitatory synaptic transmission and regulate synaptic plasticity in the central nervous system, but their dysregulation is also implicated in numerous brain disorders. Here, we describe GluN2A-selective negative allosteric modulators (NAMs) that inhibit NMDA receptors by stabilizing the apo state of the GluN1 ligand-binding domain (LBD), which is incapable of triggering channel gating. We describe structural determinants of NAM binding in crystal structures of the GluN1/2A LBD heterodimer, and analyses of NAM-bound LBD structures corresponding to active and inhibited receptor states reveal a molecular switch in the modulatory binding site that mediate the allosteric inhibition.

MPX-004 and MPX-007: New Pharmacological Tools to Study the Physiology of NMDA Receptors Containing the GluN2A Subunit.

GluN2A is the most abundant of the GluN2 NMDA receptor subunits in the mammalian CNS. Physiological and genetic evidence implicate GluN2A-containing receptors in susceptibility to autism, schizophrenia, childhood epilepsy and neurodevelopmental disorders such as Rett Syndrome. However, GluN2A-selective pharmacological probes to explore the therapeutic potential of targeting these receptors have been lacking.

Allosteric modulators for the treatment of schizophrenia: targeting glutamatergic networks.

Schizophrenia is a highly debilitating mental disorder which afflicts approximately 1% of the global population. Cognitive and negative deficits account for the lifelong disability associated with schizophrenia, whose symptoms are not effectively addressed by current treatments. New medicines are needed to treat these aspects of the disease.

Analysis of information flows in interaction networks: implication for drug discovery and pharmacological research.

Frequent failures of experimental medicines in clinical trials question current concepts for predicting drug-effects in the human body. Improving the probability for success in drug discovery requires a better understanding of cause-effect relationships at the organism, organ, tissue, cellular, and molecular levels, each having a different degree of complexity. Despite the longstanding realization that clinical and preclinical drug-effect information needs to be integrated for generating more accurate forecasts of drug-effects, a road map for linking these disparate sources of information currently does not exist.

Cause-effect relationships in medicine: a protein network perspective.

Current target-based drug discovery platforms are not able to predict drug efficacy and the full spectrum of drug effects in organisms. Hence, many experimental drugs do not survive the lengthy and costly process of drug development. Understanding how drugs affect cellular network structures and how the resulting signals are translated into drug effects is extremely important for the discovery of new medicines.

Drug effects viewed from a signal transduction network perspective.

Understanding how drugs affect cellular network structures and how resulting signals are translated into drug effects holds the key to the discovery of medicines. Herein we examine this cause-effect relationship by determining protein network structures associated with the generation of specific in vivo drug-effect patterns. Medicines having similar in vivo pharmacology have been identified by a comparison of drug-effect profiles of 1320 medicines.

Analysis of system structure-function relationships.

Preclinical pharmacology studies conducted with experimental medicines currently focus on assessments of drug effects attributed to a drug's putative mechanism of action. The high failure rate of medicines in clinical trials, however, underscores that the information gathered from these studies is insufficient for forecasting drug effect profiles actually observed in patients. Improving drug effect predictions and increasing success rates of new medicines in clinical trials are some of the key challenges currently faced by the pharmaceutical industry.

Analysis of drug-induced effect patterns to link structure and side effects of medicines.

The high failure rate of experimental medicines in clinical trials accentuates inefficiencies of current drug discovery processes caused by a lack of tools for translating the information exchange between protein and organ system networks. Recently, we reported that biological activity spectra (biospectra), derived from in vitro protein binding assays, provide a mechanism for assessing a molecule's capacity to modulate the function of protein-network components. Herein we describe the translation of adverse effect data derived from 1,045 prescription drug labels into effect spectra and show their utility for diagnosing drug-induced effects of medicines.

Biospectra analysis: model proteome characterizations for linking molecular structure and biological response.

Establishing quantitative relationships between molecular structure and broad biological effects has been a long-standing goal in drug discovery. Evaluation of the capacity of molecules to modulate protein functions is a prerequisite for understanding the relationship between molecular structure and in vivo biological response. A particular challenge in these investigations is to derive quantitative measurements of a molecule's functional activity pattern across different proteins.

Substituted 6-phenyl-pyridin-2-ylamines: selective and potent inhibitors of neuronal nitric oxide synthase.

The synthesis and nNOS and eNOS activity of 6-(4-(dimethylaminoalkyl)-/6-(4-(dimethylaminoalkoxy)-5-ethyl-2-methoxyphenyl)-pyridin-2-ylamines and 6-(4-(dimethylaminoalkyl)-/6-(4-(dimethylaminoalkoxy)-2,5-dimethoxyphenyl)-pyridin-2-ylamines 1-8 are described. These compounds are potent inhibitors of the human nNOS isoform.

Structure-activity relationships of potent, selective inhibitors of neuronal nitric oxide synthase based on the 6-phenyl-2-aminopyridine structure.

The synthesis and structure-activity relationships of a series of 6-phenyl-2-aminopyridines that potently and selectively inhibit the neuronal isoform of nitric oxide synthase (nNOS) are described. Compound 14bi from this series exhibits potent in vivo activity in harmaline-induced cGMP formation in rat cerebellum, a functional model of nNOS inhibition, and in the PCP-induced hypermotility model in the rat. These results suggest that 14bi may be a useful reagent for evaluating potential therapeutic applications of nNOS inhibitors in the central nervous system.