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 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".