Pharmacological evaluation of enantiomerically separated positive allosteric modulators of cannabinoid 1 receptor, GAT591 and GAT593
Bibliographic record
Abstract
Positive allosteric modulation of the type 1 cannabinoid receptor (CB1R) has substantial potential to treat both neurological and immune disorders. To date, a few studies have evaluated the structure-activity relationship (SAR) for CB1R positive allosteric modulators (PAMs). In this study, we separated the enantiomers of the previously characterized two potent CB1R ago-PAMs GAT591 and GAT593 to determine their biochemical activity at CB1R. Separating the enantiomers showed that the R-enantiomers (GAT1665 and GAT1667) displayed mixed allosteric agonist-PAM activity at CB1R while the S-enantiomers (GAT1664 and GAT1666) showed moderate activity. Furthermore, we observed that the R and S-enantiomers had distinct binding sites on CB1R, which led to their distinct behavior both in vitro and in vivo. The R-enantiomers (GAT1665 and GAT1667) produced ago-PAM effects in vitro, and PAM effects in the in vivo behavioral triad, indicating that the in vivo activity of these ligands may occur via PAM rather than agonist-based mechanisms. Overall, this study provides mechanistic insight into enantiospecific interaction of 2-phenylindole class of CB1R allosteric modulators, which have shown therapeutic potential in the treatment of pain, epilepsy, glaucoma, and Huntington’s disease.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".