Oligomerization of μ- and δ-Opioid Receptors
Bibliographic record
Abstract
The existence of dimers and oligomers for many G protein-coupled receptors has been described by us and others. Since many G protein-coupled receptor subtypes are highly homologous to each other, we examined whether closely related receptors may interact with each other directly and thus have the potential to create novel signaling units. Using mu- and delta-opioid receptors, we show that each receptor expressed individually was pharmacologically distinct and could be visualized following electrophoresis as monomers, homodimers, homotetramers, and higher molecular mass oligomers. When mu- and delta-opioid receptors were coexpressed, the highly selective synthetic agonists for each had reduced potency and altered rank order, whereas endomorphin-1 and Leu-enkephalin had enhanced affinity, suggesting the formation of a novel binding pocket. No heterodimers were visualized in the membranes coexpressing mu- and delta-receptors by the methods available. However, hetero-oligomers were identified by the ability to co-immunoprecipitate mu-receptors with delta-receptors and vice versa using differentially epitope-tagged receptors. In contrast to the individually expressed mu- and delta-receptors, the coexpressed receptors showed insensitivity to pertussis toxin and continued signal transduction, likely due to interaction with a different subtype of G protein. In this study, we provide, for the first time, evidence for the direct interaction of mu- and delta-opioid receptors to form oligomers, with the generation of novel pharmacology and G protein coupling properties.
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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) | 0.001 | 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".