Genetically encoded intrabody sensors illuminate structural and functional diversity in GPCR-β-arrestin complexes
Bibliographic record
Abstract
Abstract Interaction of β-arrestins (βarrs) upon agonist-stimulation is a hallmark of G protein-coupled receptors (GPCRs) resulting in receptor desensitization, endocytosis and signaling. Although overall functional roles of βarrs are typically believed to be conserved across different receptors, emerging data now clearly unveils receptor-specific functional contribution of βarrs. The underlying mechanism however remains mostly speculative and represents a key missing link in our current understanding of GPCR signaling and regulatory paradigms. Here, we develop synthetic intrabody-based conformational sensors that help us visualize the assembly and trafficking of GPCR-βarr1 complexes in cellular context for a broad set of receptors with spatio-temporal resolution. Surprisingly, these conformational sensors reveal a previously unappreciated level of diversity in GPCR-βarr complexes that extends beyond the current framework of affinity-based classification and phosphorylation-code-based interaction patterns. More importantly, this conformational diversity arising from spatial signature of phosphorylation sites manifests directly in the form of distinct functional outcomes, including even opposite contribution of βarrs in signal-transduction for different receptors. Taken together, these findings uncover that despite an overall similar interaction and trafficking patterns; critical structural and functional differences exist in βarr complexes for different GPCRs that define and fine-tune receptor-specific downstream responses.
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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) | 0.001 | 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".