Localized apelin-17 analogue-bicelle interactions as a facilitator of membrane-catalyzed receptor recognition and binding
Bibliographic record
Abstract
The apelinergic system encompasses two peptide ligand families, apelin and apela, along with the apelin receptor (AR or APJ), a class A G-protein-coupled receptor. This system has diverse physiological effects, including modulating heart contraction, vasodilation/constriction, glucose regulation, and vascular development, with involvement in a variety of pathological conditions. Apelin peptides have been previously shown to interact with and become structured upon binding to anionic micelles, consistent with a membrane-catalyzed mechanism of ligand-receptor binding. To overcome the challenges of observing nuclear magnetic resonance (NMR) spectroscopy signals of a dilute peptide in biological environments, 19F NMR spectroscopy, including diffusion ordered spectroscopy (DOSY) and saturation transfer difference (STD) experiments, was used herein to explore the membrane-interactive behaviour of apelin. NMR-optimized apelin-17 analogues with 4-trifluoromethyl-phenylalanine at various positions were designed and tested for bioactivity through ERK activation in stably-AR transfected HEK 293 T cells. Far-UV circular dichroism (CD) spectropolarimetry and 19F NMR spectroscopy were used to compare the membrane interactions of these analogues with unlabelled apelin-17 in both zwitterionic/neutral and net-negative bicelle conditions. Each analogue binds to bicelles with relatively weak affinity (i.e., in fast exchange on the NMR timescale), with preferential interactions observed at the cationic residue-rich N-terminal and mid-length regions of the peptide leaving the C-terminal end unencumbered for receptor recognition, enabling a membrane-anchored fly-casting mechanism of peptide search for the receptor. In all, this study provides further insight into the membrane-interactive behaviour of an important bioactive peptide, demonstrating interactions and biophysical behaviour that cannot be neglected in therapeutic design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".