The effect of phosphorylation on arrestin–rhodopsin interaction in the squid visual system
Bibliographic record
Abstract
Invertebrate visual opsins are G protein-coupled receptors coupled to retinoid chromophores that isomerize reversibly between inactive rhodopsin and active metarhodopsin upon absorption of photons of light. The squid visual system has an arrestin protein that binds to metarhodopsin to block signaling to Gq and activation of phospholipase C. Squid rhodopsin kinase (SQRK) can phosphorylate both metarhodopsin and arrestin, a dual role that is unique among the G protein-coupled receptor kinases. The sites and role of arrestin phosphorylation by SQRK were investigated here using recombinant proteins. Arrestin was phosphorylated on serine 392 and serine 397 in the C-terminus. Unphosphorylated arrestin bound to metarhodopsin and phosphorylated metarhodopsin with similar high affinities (Kd 33 and 21 nM respectively), while phosphorylation of arrestin reduced the affinity 3- to 5-fold (Kd 104 nM). Phosphorylation of metarhodopsin slightly increased the dissociation of arrestin observed during a 1 hour incubation. Together these studies suggest a unique role for SQRK in phosphorylating both receptor and arrestin and inhibiting the binding of these two proteins in the squid visual system. Invertebrate visual systems are inactivated by arrestin binding to metarhodopsin that does not require receptor phosphorylation. Here we show that squid rhodopsin kinase phosphorylates arrestin on two serines (S392,S397) in the C-terminus and phosphorylation decreases the affinity of arrestin for squid metarhodopsin. Metarhodopsin phosphorylation has very little effect on arrestin binding but does increase arrestin dissociation.
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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".