Identification of 5-HT2A receptor signaling pathways associated with psychedelic potential
Bibliographic record
Abstract
Abstract Serotonergic psychedelics possess considerable therapeutic potential. Although 5-HT 2A receptor activation mediates psychedelic effects, prototypical psychedelics activate both 5-HT 2A -Gq/11 and β-arrestin2 transducers, making their respective roles unclear. To elucidate this, we develop a series of 5-HT 2A -selective ligands with varying Gq efficacies, including β-arrestin-biased ligands. We show that 5-HT 2A -Gq but not 5-HT 2A -β-arrestin2 recruitment efficacy predicts psychedelic potential, assessed using head-twitch response (HTR) magnitude in male mice. We further show that disrupting Gq-PLC signaling attenuates the HTR and a threshold level of Gq activation is required to induce psychedelic-like effects, consistent with the fact that certain 5-HT 2A partial agonists (e.g., lisuride) are non-psychedelic. Understanding the role of 5-HT 2A Gq-efficacy in psychedelic-like psychopharmacology permits rational development of non-psychedelic 5-HT 2A agonists. We also demonstrate that β-arrestin-biased 5-HT 2A receptor agonists block psychedelic effects and induce receptor downregulation and tachyphylaxis. Overall, 5-HT 2A receptor Gq-signaling can be fine-tuned to generate ligands distinct from classical psychedelics.
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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 | 0.000 |
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".