Binding Interactions of Dopamine and Apomorphine in D2High and D2Low States of Human Dopamine D2 Receptor Using Computational and Experimental Techniques
Bibliographic record
Abstract
We have recently reported G-protein coupled receptor (GPCR) model structures for the active and inactive states of the human dopamine D2 receptor (D2R) using adrenergic crystal structures as templates. Since the therapeutic concentrations of dopamine agonists that suppress the release of prolactin are the same as those that act at the high-affinity state of the D2 receptor (D2High), D2High in the anterior pituitary gland is considered to be the functional state of the receptor. In addition, the therapeutic concentrations of anti-Parkinson drugs are also related to the dissociation constants in the D2High form of the receptor. The discrimination between the high- and low-affinity (D2Low) components of the D2R is not obvious and requires advanced computer-assisted structural biology investigations. Therefore, in this work, the derived D2High and D2Low receptor models (GPCR monomer and dimer three-dimensional structures) are used as drug-binding targets to investigate binding interactions of dopamine and apomorphine. The study reveals a match between the experimental dissociation constants of dopamine and apomorphine at their high- and low-affinity sites of the D2 receptor in monomer and dimer and their calculated dissociation constants. The allosteric receptor-receptor interaction for dopamine D2R dimer is associated with the accessibility of adjacent residues of transmembrane region 4. The measured negative cooperativity between agonist ligand at dopamine D2 receptor is also correctly predicted using the D2R homodimerization model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".