The Signaling and Pharmacology of the Dopamine D1 Receptor
Bibliographic record
Abstract
The dopamine D1 receptor (D1R) is a Gαs/olf-coupled GPCR that is expressed in the midbrain and forebrain, regulating motor behavior, reward, motivational states, and cognitive processes. Although the D1R was initially identified as a promising drug target almost 40 years ago, the development of clinically useful ligands has until recently been hampered by a lack of suitable candidate molecules. The emergence of new non-catechol D1R agonists, biased agonists, and allosteric modulators has renewed clinical interest in drugs targeting this receptor, specifically for the treatment of motor impairment in Parkinson's Disease, and cognitive impairment in neuropsychiatric disorders. To develop better therapeutics, advances in ligand chemistry must be matched by an expanded understanding of D1R signaling across cell populations in the brain, and in disease states. Depending on the brain region, the D1R couples primarily to either Gαs or Gαolf through which it activates a cAMP/PKA-dependent signaling cascade that can regulate neuronal excitability, stimulate gene expression, and facilitate synaptic plasticity. However, like many GPCRs, the D1R can signal through multiple downstream pathways, and specific signaling signatures may differ between cell types or be altered in disease. To guide development of improved D1R ligands, it is important to understand how signaling unfolds in specific target cells, and how this signaling affects circuit function and behavior. In this review, we provide a summary of D1R-directed signaling in various neuronal populations and describe how specific pathways have been linked to physiological and behavioral outcomes. In addition, we address the current state of D1R drug development, including the pharmacology of newly developed non-catecholamine ligands, and discuss the potential utility of D1R-agonists in Parkinson's Disease and cognitive impairment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".