Dissecting the allosteric networks governing agonist efficacy and potency in G protein-coupled receptors
Bibliographic record
Abstract
Abstract G protein-coupled receptors (GPCRs) translate binding of extracellular ligands into intracellular responses through conformational changes. Ligand properties are described by the maximum response (efficacy) and the agonist concentration at half-maximal response (potency). Integrating structural changes with pharmacological properties remains challenging and has not yet been performed at the resolution of individual amino acids. We use epinephrine and β2-adrenergic receptor as a model to integrate residue-level pharmacology data with intramolecular residue contact data describing receptor activation. This unveils the allosteric networks driving ligand efficacy and potency. We provide detailed insights into how structural rearrangements are linked to fundamental pharmacological properties at single-residue level in a receptor-ligand system. Our approach can be used to determine such pharmacological networks for any receptor-ligand complex.
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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 | 0.000 |
| 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".