Insight into the Mechanism of Dopamine D1-like Receptor Activation
Bibliographic record
Abstract
A chimeric D1A dopaminergic receptor harboring the cytoplasmic tail (CT) of the D1B subtype (D1A-CTB) has been used previously to show that CT imparts high dopamine (DA) affinity and constitutive activity to the D1B receptors. However, the D1A-CTB chimera, unlike the D1B subtype, exhibits a significantly lower DA potency for stimulating adenylyl cyclase and a drastically lower maximal binding capacity (Bmax). Here, using a functional complementation of chimeric D1-like receptors, we have identified the human D1B receptor regions regulating the intramolecular relationships that lead to an increased DA potency and contribute to Bmax. We demonstrate that the addition of variant residues of the third extracellular loop (EL3) of the human D1B receptor into D1A-CTB chimera leads to a constitutively active mutant receptor displaying an increased DA affinity, potency, and Bmax. These results strongly suggest that constitutively active D1-like receptors can adopt multiple active conformations, notably one that confers increased DA affinity with decreased DA potency and Bmax and another that imparts increased DA affinity with a strikingly increased DA potency and Bmax. Overall, we show that a novel molecular interplay between EL3 and CT regulates multiple active conformations of D1-like receptors and may have potential implications for other G protein-coupled receptor classes.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".