Characterization of Urotensin-II Receptor Structural Domains Involved in the Recognition of U-II, URP, and Urantide
Bibliographic record
Abstract
Urotensin-II (U-II) and urotensin-II-related peptide (URP) are potent vasoconstrictors, and this action is mediated through a G protein-coupled receptor identified as UT. This receptor is expressed abundantly in the mammalian cardiovasculature, and the effects of U-II and URP can be blocked with urantide, a selective antagonist. Thus, we carried out a study with the aim to characterize the conformational arrangement of the three extracellular loops of UT as well as the transmembrane domains III and IV. Secondary structures of the synthetic receptor fragments were determined using circular dichroism (CD) spectroscopy in a variety of solvent and micelle conditions. Spectra showed that all receptor segments but not the extracellular loop I exhibited a propensity for adopting the alpha-helix folding. Furthermore, using surface plasmon resonance (SPR) technology, we measured the binding affinities of the ligands, U-II, URP, and urantide toward the UT extracellular segments. SPR data showed that both U-II and URP bind extracellular loops II and III with similar affinities, whereas none of these two ligands were able to interact with the extracellular loop I. Moreover, the binding of urantide was observed only with the second extracellular loop. These results imply that U-II and URP but not urantide would bind to UT according to a common pattern. Also, the correlation of the CD spectral information with the affinity data suggested that the adoption of a helical geometry in UT, by extracellular loops II and III, might be essential for favoring the binding of ligands.
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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".