Interaction of the <i>N</i>-AcAβ(13–23)NH<sub>2</sub> segment of the beta amyloid peptide with beta-sheet-blocking peptides: site and edge specificity
Bibliographic record
Abstract
The region encompassing residues 13–23 of the amyloid beta peptide (Aβ(13–23)) of Alzheimer’s disease is the self-recognition site that initiates toxic oligomerization and fibrillization and also is the site of interaction of Aβ with many other proteins. We describe herein a study by molecular dynamics of the complexes formed by R (= N-AcAβ(13–23)NH2(N-CH3C(O)HHQKLVFFAEDNH2)) with several pseudopeptides designed to form β-sheets with Aβ(1-40,42) and prevent oligomer and fibril formation. Adhesion to both edges of the R β-strand is examined by structure analysis. Umbrella sampling along a dissociation pathway reveals approximate free energies of binding in the submicromolar range. One of the three pseudopeptides binds strongly to one edge of the R β-strand and another to the opposite edge, while the third displays strong binding to both edges. It is desirable to block both edges of the self-recognition site of Aβ to prevent oligomer formation. The study reveals that this may be accomplished by a single pseudopeptide or two in combination. Thus the pseudopeptides, used singly or in pairs, may be competitive inhibitors of Aβ oligomerization at stoichiometric concentrations.
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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".