Functional Selectivity in GPCR Signaling: Understanding the Full Spectrum of Receptor Conformations
Bibliographic record
Abstract
The great versatility of G protein-coupled receptors (GPCRs), in terms of both their ability to bind different types of ligands and initiate a large number of distinct cellular signaling events, remains incompletely understood. In recent years, the classical view of the nature and consequences of ligand binding to GPCRs has dramatically changed. The notion of functional selectivity, achieved through both biased ligands and allosteric modulators, has brought substantial new insight into our comprehension of the pluridimensionality of signaling achieved by GPCRs. Moreover, receptor heterodimerization adds another important dimension to the diversity of cellular responses controlled by GPCRs. Here, we review these considerations and discuss how they will impact the design of improved therapeutics. Keywords: GPCR, ligand-directed signaling, functional selectivity, biased ligand, allosterism, dimer, rhodopsin, Neutral Antagonist, Allosteric modulator, Bitopic ligand, metabotropic glutamate receptors
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".