Intrinsic bias at non-canonical, β-arrestin-coupled seven transmembrane receptors
Bibliographic record
Abstract
Abstract G protein-coupled receptors (GPCRs) are typically characterized by their seven transmembrane (7TM) architecture, and interaction with two universal signal-transducers namely, the heterotrimeric G-proteins and β-arrestins (βarrs). Synthetic ligands and receptor mutants have been designed to elicit transducer-coupling preferences and distinct downstream signaling outcomes for many GPCRs. This raises the question if some naturally-occurring 7TMRs may selectively engage one of these two signal-transducers, even in response to their endogenous agonists. Although there are scattered hints in the literature that some 7TMRs lack G-protein coupling but interact with βarrs, an in-depth understanding of their transducer-coupling preference, GRK-engagement, downstream signaling and structural mechanism remains elusive. Here, we use an array of cellular, biochemical and structural approaches to comprehensively characterize two non-canonical 7TMRs namely, the human decoy D6 receptor (D6R) and the human complement C5a receptor (C5aR2), in parallel with their canonical GPCR counterparts, CCR2 and C5aR1, respectively. We discover that D6R and C5aR2 couple exclusively to βarrs, exhibit distinct GRK-preference, and activate non-canonical downstream signaling partners. We also observe that βarrs, in complex with these receptors, adopt distinct conformations compared to their canonical GPCR counterparts despite being activated by a common natural agonist. Our study therefore establishes D6R and C5aR2 as bona-fide arrestin-coupled receptors (ACRs), and provides important insights into their regulation by GRKs and downstream signaling with direct implications for biased agonism.
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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) | 0.002 | 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".