Subtypes of the Somatostatin Receptor Assemble as Functional Homo- and Heterodimers
Bibliographic record
Abstract
The existence of receptor dimers has been proposed for several G protein-coupled receptors. However, the question of whether G protein-coupled receptor dimers are necessary for activating or modulating normal receptor function is unclear. We address this question with somatostatin receptors (SSTRs) of which there are five distinct subtypes. By using transfected mutant and wild type receptors, as well as endogenous receptors, we provide pharmacological, biochemical, and physical evidence, based on fluorescence resonance energy transfer analysis, that activation by ligand induces SSTR dimerization, both homo- and heterodimerization with other members of the SSTR family, and that dimerization alters the functional properties of the receptor such as ligand binding affinity and agonist-induced receptor internalization and up-regulation. Double label confocal fluorescence microscopy showed that when SSTR1 and SSTR5 subtypes were coexpressed in Chinese hamster ovary-K1 cells and treated with agonist they underwent internalization and were colocalized in cytoplasmic vesicles. SSTR5 formed heterodimers with SSTR1 but not with SSTR4 suggesting that heterodimerization is a specific process that is restricted to some but not all receptor subtype combinations. Direct protein interaction between different members of the SSTR subfamily defines a new level of molecular cross-talk between subtypes of the SSTR and possibly related receptor families.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".