Metabotropic glutamate receptor 5 modulators and their potential therapeutic applications
Bibliographic record
Abstract
Extensive research into the functions of glutamate and glutamate receptors in the CNS has shown an essential role of metabotropic glutamate (mGlu) receptors not only in normal brain functions but also in neurological and psychiatric disorders. The precise functions of these receptors remain undefined and progress toward understanding their functions had been hampered by the lack of selective ligands with appropriate pharmacokinetic properties. The Group I mGlu receptors, comprising mGlu1 and mGlu5 receptors, are well positioned to regulate and fine-tune neuronal excitability and synaptic transmission through its modulation of various signal transduction pathways and interactions with other transmitter systems. Therefore, the mGlu5 receptor may be an important therapeutic target for the treatment of disorders of the CNS. The discovery of MPEP, a non-competitive mGluR5 antagonist, provided a potent, selective, systemically active tool compound for proof-of-concept studies in animal models of various disease states. Considerable advances have been made since the applications of glutamate receptor modulators was reviewed by Sabbatini and Micheli in this journal in late 2004. Most intriguing is the increased understanding of the mechanism and pathophysiology of mGlu5 receptors in the treatment of CNS diseases. The importance of mGlu5 receptors is manifested by the growing numbers of patents filed and scientific papers published in recent years. In the present patent review, compound series have been catagorized as antagonists/inhibitors or modulators/potentiators, according to the claims in the respective patent applications. Claims that relate to and specify group I mGluRs have been included in a separate section, while claims for specified compound series for the treatment of glutamate receptor-mediated disorders in general have not been included. Primary literature has been referenced when information on compound series from the patent literature could be supplemented with, for example, SAR or pharmacological data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".