Synergistically acting agonists and antagonists of G protein–coupled receptors prevent photoreceptor cell degeneration
Bibliographic record
Abstract
Photoreceptor cell degeneration leads to visual impairment and blindness in several types of retinal disease. However, the discovery of safe and effective therapeutic strategies conferring photoreceptor cell protection remains challenging. Targeting distinct cellular pathways with low doses of different drugs that produce a functionally synergistic effect could provide a strategy for preventing or treating retinal dystrophies. We took a systems pharmacology approach to identify potential combination therapies using a mouse model of light-induced retinal degeneration. We showed that a combination of U.S. Food and Drug Administration-approved drugs that act on different G protein (heterotrimeric guanine nucleotide-binding protein)-coupled receptors (GPCRs) exhibited synergistic activity that protected retinas from light-induced degeneration even when each drug was administered at a low dose. In functional assays, the combined effects of these drugs were stimulation of Gi/o signaling by activating the dopamine receptors D2R and D4R, as well as inhibition of Gs and Gq signaling by antagonizing D1R and the α1A-adrenergic receptor ADRA1A, respectively. Moreover, transcriptome analyses demonstrated that such combined GPCR-targeted treatments preserved patterns of retinal gene expression that were more similar to those of the normal retina than did higher-dose monotherapy. Our study thus supports a systems pharmacology approach to identify treatments for retinopathies, an approach that could extend to other complex disorders.
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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) | 0.001 | 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 | 0.001 |
| 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".