Distinct Helix Propensities and Membrane Interactions of Human and Rat IAPP<sub>1–19</sub> Monomers in Anionic Lipid Bilayers
Bibliographic record
Abstract
Islet amyloid polypeptide, IAPP or amylin, is a 37-residue peptide hormone coexpressed with insulin by pancreatic β-cells. The aggregation of human IAPP (hIAPP) into amyloid deposits is associated with type II diabetes. Substantial evidence suggests that the interaction of anionic membranes with hIAPP may facilitate peptide aggregation and the N-terminal 1-19 fragment (IAPP(1-19)) plays an important role in peptide-membrane interaction. As a first step to understand how structural differences between human and rat IAPP peptides in membranes may influence the later oligomerization process, we have investigated the structures and orientations of hIAPP(1-19) and the less toxic rIAPP(1-19) (i.e., the H18R mutant of hIAPP(1-19)) monomers in anionic POPG bilayers by performing replica exchange molecular dynamics (REMD) simulations. On the basis of ∼20 μs REMD simulations started from a random coil conformation of the peptide placed in water, we find that unfolded h(r)IAPP(1-19) can insert into the bilayers and the membrane-bound peptide stays mainly at the lipid head-tail interface. hIAPP(1-19) displays higher helix propensity than rIAPP(1-19), especially in the L12-L16 region. The helix is oriented parallel to the bilayer surface and buried in the membrane 0.3-0.8 nm below the phosphorus atoms, consistent with previous electron paramagnetic resonance data. The helical conformation is an amphiphilic helix with its hydrophilic and hydrophobic faces pointing, respectively, to the lipid head and tail regions. The H18R substitution enhances the electrostatic interactions of IAPP(1-19) with the membrane, while it weakens the intrapeptide interactions crucial for helix formation, thus leading to lower helix propensity of rIAPP(1-19). Implications of our simulation results on the membrane-mediated IAPP(1-19) oligomerization are discussed.
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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 | 0.001 |
| 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".