Behavioral Effects of a Potential Novel TAAR1 Antagonist
Bibliographic record
Abstract
TAAR1 is a G-protein coupled receptor expressed in the monoaminergic regions of the brain, and represents a potential novel therapeutic target for the treatment of neurological disorders. While selective agonists for TAAR1 have been successfully identified, only one high affinity TAAR1 antagonist has been described thus far. We previously identified four potential low potency TAAR1 antagonists through an in silico screen on a TAAR1 homology model. One of the identified antagonists (compound 22) was predicted to have favourable physicochemical properties, which would allow the drug to cross the blood brain barrier. In vivo studies were therefore carried out and showed that compound 22 potentiates amphetamine- and cocaine-mediated locomotor activity, consistent with behaviours observed in TAAR1-KO animals. In order to assess whether the effects of compound 22 were mediated through TAAR1, experiments were carried out on TAAR1-KO mice. The results showed that compound 22 is able to enhance amphetamine- and cocaine-mediated locomotor activity, even in TAAR1-KO mice, suggesting that the in vivo effects of this compound are not mediated by TAAR1. In collaboration with Psychoactive Drug Screening Program, we attempted to determine the targets for compound 22. PDSP results suggested several potential targets for compound 22 including, the dopamine, norepinephrine and serotonin transporters; as well as sigma 1 and 2 receptors. Our follow-up studies using heterologous cell systems showed that the dopamine transporter is not a target of compound 22. Therefore, the biological target of compound 22 mediating its psychoactive effects still remains unknown.
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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) | 0.003 | 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".