Positive allosteric modulation of the cannabinoid CB<sub>1</sub> receptor potentiates endocannabinoid signalling and changes ERK1/2 phosphorylation kinetics
Bibliographic record
Abstract
Abstract Background and Purpose Activation of CB1 by exogenous agonists causes adverse effects in vivo. Positive allosteric modulation may offer improved therapeutic potential and a reduced on‐target adverse effect profile compared with orthosteric agonists, due to reduced desensitisation/tolerance, but this has not been directly tested. This study investigated the ability of PAMs/ago‐PAMs to induce receptor regulation pathways, including desensitisation and receptor internalisation. Experimental Approach Bioluminescence resonance energy transfer (BRET) assays in HEK293 cells were performed to investigate G protein dissociation, ERK1/2 phosphorylation and β‐arrestin 2 translocation, while immunocytochemistry was performed to measure internalisation of CB1 in response to the PAMs ZCZ011, GAT229 and ABD1236 alone and in combination with the orthosteric agonists AEA, 2‐AG, and AMB‐FUBINACA. Key Results ZCZ011, GAT229 and ABD1236 were allosteric agonists in all pathways tested. The ago‐PAM ZCZ011 induced a biphasic ERK1/2 phosphorylation time course compared to transient activation by orthosteric agonists. In combination with 2‐AG but not AEA or AMB‐FUBINACA, ZCZ011 and ABD1236 caused the transient peak of ERK1/2 phosphorylation to become sustained. All PAMs increased the potency and efficacy of AEA‐induced signalling in all pathways tested; however, no notable potentiation of 2‐AG or AMB‐FUBINACA was observed. Conclusion and Implications Ago‐PAMs can potentiate endocannabinoid CB1 agonism by AEA to a larger extent compared with 2‐AG. However, all compounds were found to be allosteric agonists and induce activation of CB1 in the absence of endocannabinoid, including β‐arrestin 2 recruitment and internalisation. Thus, the spatiotemporal signalling of endogenous cannabinoids will not be retained in vivo.
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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) | 0.003 | 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".