Enantiospecific Allosteric Modulation of Cannabinoid 1 Receptor
Bibliographic record
Abstract
The cannabinoid 1 receptor (CB1R) is one of the most widely expressed metabotropic G protein-coupled receptors in brain, and its participation in various (patho)physiological processes has made CB1R activation a viable therapeutic modality. Adverse psychotropic effects limit the clinical utility of CB1R orthosteric agonists and have promoted the search for CB1R positive allosteric modulators (PAMs) with the promise of improved drug-like pharmacology and enhanced safety over typical CB1R agonists. In this study, we describe the synthesis and in vitro and ex vivo pharmacology of the novel allosteric CB1R modulator GAT211 (racemic) and its resolved enantiomers, GAT228 ( R ) and GAT229 ( S ). GAT211 engages CB1R allosteric site(s), enhances the binding of the orthosteric full agonist [ 3 H]CP55,490, and reduces the binding of the orthosteric antagonist/inverse agonist [ 3 H]SR141716A. GAT211 displayed both PAM and agonist activity in HEK293A and Neuro2a cells expressing human recombinant CB1R (hCB1R) and in mouse-brain membranes rich in native CB1R. GAT211 also exhibited a strong PAM effect in isolated vas deferens endogenously expressing CB1R. Each resolved and crystallized GAT211 enantiomer showed a markedly distinctive pharmacology as a CB1R allosteric modulator. In all biological systems examined, GAT211’s allosteric agonist activity resided with the R- (+)-enantiomer (GAT228), whereas its PAM activity resided with the S -(−)-enantiomer (GAT229), which lacked intrinsic activity. These results constitute the first demonstration of enantiomer-selective CB1R positive allosteric modulation and set a precedent whereby enantiomeric resolution can decisively define the molecular pharmacology of a CB1R allosteric ligand.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".