Recent Advances in Non-Competitive mGlu5 Receptor Antagonists and their Potential Therapeutic Applications
Bibliographic record
Abstract
Extensive research into the functions of glutamate and glutamate receptors in the central nervous system (CNS) has shown an essential role of metabotropic glutamate (mGlu) receptors 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 has been hampered by the lack of selective ligands with appropriate pharmacokinetic properties. The Group I mGlu receptor, mGlu5, is 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 central nervous system. The discovery of MPEP 3, a non-competitive mGlu5 receptor antagonist, provided a potent, selective, systemically active tool compound for proof of concept studies in animal models of various disease states. These studies have led to greater understanding of possible therapeutic applications of mGlu5 receptor antagonists in recent years, suggesting their use in a number of disease states, including chronic pain, various psychiatric and neurological disorders, substance abuse and withdrawal, obesity and gastroesophageal reflux disease (GERD). Together, these findings have intensified efforts to find other non-competitive mGlu5 receptor antagonists and have led to the discovery of several second-generation compounds, a few of which are in preclinical evaluations. There have been several recent reviews on mGlu receptor. This article highlights recent efforts on the design, synthesis and development of novel, non-competitive mGlu5 receptor antagonists and studies to understand their in vitro mechanisms of action and in vivo pharmacological profiles. Emphasis is also given to recent advances in the potential therapeutic applications of non-competitive mGlu5 receptor antagonists.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".