Conformational Dynamics and Stability of U-Shaped and S-Shaped Amyloid β Assemblies
Bibliographic record
Abstract
Alzheimer’s disease is the most fatal neurodegenerative disorder characterized by the aggregation and deposition of Amyloid β (Aβ) oligomers in the brain of patients. Two principal variants of Aβ exist in humans: Aβ1–40 and Aβ1–42. The former is the most abundant in the plaques, while the latter is the most toxic species and forms fibrils more rapidly. Interestingly, fibrils of Aβ1–40 peptides can only assume U-shaped conformations while Aβ1–42 can also arrange as S-shaped three-stranded chains, as recently discovered. As alterations in protein conformational arrangement correlate with cell toxicity and speed of disease progression, it is important to characterize, at molecular level, the conformational dynamics of amyloid fibrils. In this work, Replica Exchange Molecular Dynamics simulations were carried out to compare the conformational dynamics of U-shaped and S-shaped Aβ17–42 small fibrils. Our computational results provide support for the stability of the recently proposed S-shaped model due to the maximized interactions involving the C-terminal residues. On the other hand, the U-shaped motif is characterized by significant distortions resulting in a more disordered assembly. Outcomes of our work suggest that the molecular architecture of the protein aggregates might play a pivotal role in formation and conformational stability of the resulting fibrils.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".