Headgroup-Dependent Membrane Catalysis of Apelin−Receptor Interactions Is Likely
Bibliographic record
Abstract
Apelin is the peptidic ligand for the G-protein-coupled receptor APJ. The apelin-APJ system is important in cardiovascular regulation, fluid homeostasis, and angiogenesis, among other roles. In this study, we investigate interactions between apelin and membrane-mimetic micelles of the detergents sodium dodecyl sulfate (SDS), dodecylphosphocholine (DPC), and 1-palmitoyl-2-hydroxy-sn-glycero-3-[phospho-rac-(1-glycerol)] (LPPG). Far-ultraviolet circular dichroism spectropolarimetry and diffusion-ordered spectroscopy indicate that apelin peptides bind to micelles of the anionic detergents SDS and LPPG much more favorably than to zwitterionic DPC micelles. Nuclear magnetic resonance spectroscopy allowed full characterization of the interactions of apelin-17 with SDS micelles. Titration with paramagnetic agents and structural determination of apelin-17 in SDS indicate that R6-K12 is highly structured, with R6-L9 directly interacting with headgroups of the micelle. Type I beta-turns are initiated between R6 and L9, and a well-defined type IV beta-turn is initiated at S10. Furthermore, binding of apelin-17 to SDS micelles causes structuring of M15-F17, with no evidence for direct binding of this region to the micelles. These results are placed into the context of the membrane catalysis hypothesis for peptide-receptor binding, and a hypothetical mechanism of APJ binding and activation by apelin is advanced.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".