Effect of the Disulfide Bond on the Monomeric Structure of Human Amylin Studied by Combined Hamiltonian and Temperature Replica Exchange Molecular Dynamics Simulations
Bibliographic record
Abstract
The human Islet amyloid polypeptide (hIAPP or amylin) is a 37-residue peptide hormone that is normally cosecreted with insulin by the pancreatic beta-cells. In patients with type 2 diabetes, hIAPP deposits as amyloid fibrils in the extracellular spaces of the pancreatic islets. Recent experimental studies show that the intramolecular disulfide bond between Cys2 and Cys7 plays a central role in the process of fibril formation. However, the effect of the disulfide bond on the intrinsic structural properties of monomeric hIAPP is yet to be determined. In this study, we characterize the atomic structure and the thermodynamics of full-length hIAPP in the presence and absence of a disulfide bond using extensive combined Hamiltonian and temperature replica exchange molecular dynamics simulations (HT-REMD) with a coarse grained protein force field. Our simulations show that HT-REMD is more efficient in sampling than temperature REMD. On the basis of a total simulation time of 28 mus, we find that, although native hIAPP (in the presence of a disulfide bond) essentially adopts a disordered conformation in solution, consistent with the signal measured by ultraviolet-circular dichroism (UV-CD) spectroscopy, it also transiently samples alpha-helical structure for residues 5-16. In comparison with the N-terminal region, the C-terminal region is highly disordered and populates a much lesser content of isolated beta-strand conformation for residues 22-26 and 30-35. Moreover, the absence of the disulfide bond greatly decreases the extent of helix formed throughout residues 5-9 in favor of random coil and beta-sheet structure. Implications of the stabilization of N-terminal helical structure by disulfide bond on the initialization of hIAPP amyloid formation 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".