Palmitoylation of the V2 Vasopressin Receptor Carboxyl Tail Enhances β-Arrestin Recruitment Leading to Efficient Receptor Endocytosis and ERK1/2 Activation
Bibliographic record
Abstract
A large number of G protein-coupled receptors are palmitoylated on cysteine residues located in their carboxyl tail, but the general role of this post-translational modification remains poorly understood. Here we show that preventing palmitoylation of the V2 vasopressin receptor, by site-directed mutagenesis of cysteines 341 and 342, significantly delayed and decreased both agonist-promoted receptor endocytosis and mitogen-activated protein kinase activation. Pharmacological blockade of receptor endocytosis is without effect on the vasopressin-stimulated mitogen-activated protein kinase activity, excluding the possibility that the reduced kinase activation mediated by the palmitoylation-less mutant could result from altered receptor endocytosis. In contrast, two dominant negative mutants of beta-arrestin which inhibit receptor endocytosis also attenuated vasopressin-stimulated mitogen-activated protein kinase activity, suggesting that the scaffolding protein, beta-arrestin, represents the common link among receptor palmitoylation, endocytosis, and kinase activation. Coimmunoprecipitation and bioluminescence resonance energy transfer experiments confirmed that inhibiting receptor palmitoylation considerably reduced the vasopressin-stimulated recruitment of beta-arrestin to the receptor. Interestingly, the changes in beta-arrestin recruitment kinetics were similar to those observed for vasopressin-stimulated receptor endocytosis and mitogen-activated protein kinase activation. Taken together the results indicate that palmitoylation enhances the recruitment of beta-arrestin to the activated V2 vasopressin receptor thus facilitating processes requiring the scaffolding action of beta-arrestin.
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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) | 0.001 | 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".