d-Amino Acid Pseudopeptides as Potential Amyloid-Beta Aggregation Inhibitors
Bibliographic record
Abstract
A causative factor for neurotoxicity associated with Alzheimer’s disease is the aggregation of the amyloid-β (Aβ) peptide into soluble oligomers. Two all d-amino acid pseudo-peptides, SGB1 and SGD1, were designed to stop the aggregation. Molecular dynamics (MD) simulations have been carried out to study the interaction of the pseudo-peptides with both Aβ13–23 (the core recognition site of Aβ) and full-length Aβ1–42. Umbrella sampling MD calculations have been used to estimate the free energy of binding, ∆G, of these peptides to Aβ13–23. The highest ∆Gbinding is found for SGB1. Each of the pseudo-peptides was also docked to Aβ1–42 and subjected up to seven microseconds of all atom molecular dynamics simulations. The resulting structures lend insight into how the dynamics of Aβ1–42 are altered by complexation with the pseudo-peptides and confirmed that SGB1 may be a better candidate for developing into a drug to prevent Alzheimer’s disease.
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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".