G protein-coupled receptor-effector macromolecular membrane assemblies (GEMMAs)
Bibliographic record
Abstract
G protein-coupled receptors (GPCRs) are the largest group of receptors involved in cellular signaling across the plasma membrane and a major class of drug targets. The canonical model for GPCR signaling involves three components - the GPCR, a heterotrimeric G protein and a proximal plasma membrane effector - that have been generally thought to be freely mobile molecules able to interact by 'collision coupling'. Here, we synthesize evidence that supports the existence of GPCR-effector macromolecular membrane assemblies (GEMMAs) comprised of specific GPCRs, G proteins, plasma membrane effector molecules and other associated transmembrane proteins that are pre-assembled prior to receptor activation by agonists, which then leads to subsequent rearrangement of the GEMMA components. The GEMMA concept offers an alternative and complementary model to the canonical collision-coupling model, allowing more efficient interactions between specific signaling components, as well as the integration of the concept of GPCR oligomerization as well as GPCR interactions with orphan receptors, truncated GPCRs and other membrane-localized GPCR-associated proteins. Collision-coupling and pre-assembled mechanisms are not exclusive and likely both operate in the cell, providing a spectrum of signaling modalities which explains the differential properties of a multitude of GPCRs in their different cellular environments. Here, we explore the unique pharmacological characteristics of individual GEMMAs, which could provide new opportunities to therapeutically modulate GPCR signaling.
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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 | 0.002 | 0.002 |
| 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 | 0.004 |
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".