GRK-biased adrenergic agonists for the treatment of type 2 diabetes and obesity
Bibliographic record
Abstract
Biased agonism of G protein-coupled receptors (GPCRs) offers potential for safer medications. Current efforts have explored the balance between G proteins and β-arrestin; however, other transducers like GPCR kinases (GRKs) remain understudied. GRK2 is essential for β 2 adrenergic receptor (β 2 AR)-mediated glucose uptake, but β 2 AR agonists are considered poor clinical candidates for glycemic management due to G s /cyclic AMP (cAMP)-induced cardiac side effects and β-arrestin-dependent desensitization. Using ligand-based virtual screening and chemical evolution, we developed pathway-selective agonists of β 2 AR that prefer GRK coupling. These compounds perform well in preclinical models of hyperglycemia and obesity and demonstrate a lower potential for cardiac and muscular side effects compared with standard β 2 -receptor agonists and incretin mimetics, respectively. Furthermore, the lead candidate showed favorable pharmacokinetics and was well tolerated in a placebo-controlled clinical trial. GRK-biased β 2 AR partial agonists are thus promising oral alternatives to injectable incretin mimetics used in the treatment of type 2 diabetes and obesity.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".