RGS Proteins: Swiss Army Knives in Seven-Transmembrane Domain Receptor Signaling Networks
Bibliographic record
Abstract
Coordinated regulation of heterotrimeric guanine nucleotide-binding protein (G protein) activity is critical for the integration of information from multiple intracellular signaling networks. The human regulator of G protein signaling (RGS) protein family contains more than 35 members that are well suited for this purpose. Although all RGS proteins contain a core ~120-amino acid Galpha-interacting domain (called the RGS domain), they differ widely in size and organization of other functional domains. Architecturally complex RGS proteins contain multiple modular protein-protein interaction domains that mediate their interaction with diverse signaling effectors. Architecturally simple RGS proteins contain small amino-terminal domains; however, they show surprising versatility in the number of intracellular partners with which they interact. This Perspective focuses on RGS2, a simple RGS protein with the potential to integrate multiple signaling networks. In three recent studies, the amino-terminal domain of RGS2 was shown to interact with and regulate three different effector proteins: adenylyl cyclase, tubulin, and the cation channel TRPV6. To explain this growing list of RGS2-interacting partners, we propose two models: (i) The amino-terminal domain of RGS2 comprises several short effector protein interaction motifs; (ii) the amino-terminal domain of RGS2 adopts distinct structures to bind various targets. Whatever the precise mechanism controlling its target interactions, these studies suggest that RGS2 is a key point of integration for multiple intracellular signaling pathways, and they highlight the role of RGS proteins as dynamic, multifunctional signaling centers that coordinate a diverse range of cellular functions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".