Aza-Residue Modulation of Cyclic <scp>d</scp>,<scp>l</scp>-α-Peptide Nanotube Assembly with Enhanced Anti-Amyloidogenic Activity
Bibliographic record
Abstract
Transient soluble oligomers of amyloid-β (Aβ) are considered among the most toxic species in Alzheimer’s disease (AD). Soluble Aβ oligomers accumulate early prior to insoluble plaque formation and cognitive impairment. The cyclic d, l -α-peptide CP-2 ( 1 ) self-assembles into nanotubes and demonstrates promising anti-amyloidogenic activity likely by a mechanism involving engagement of soluble oligomers. Systematic replacement of the residues in peptide 1 with aza-amino acid counterparts was performed to explore the effects of hydrogen bonding on propensity to mitigate Aβ aggregation and toxicity. Certain azapeptides exhibited improved ability to engage, alter the secondary structure, and inhibit aggregation of Aβ. Moreover, certain azapeptides disassembled preformed Aβ fibrils and protected cells from Aβ-mediated toxicity. Substitution of the l -norleucine 3 and d -serine 6 residues in peptide 1 with aza-norleucine and aza-homoserine provided, respectively, nontoxic [azaNle 3 ]- 1 ( 4 ) and [azaHse 6 ]- 1 ( 7 ), that significantly abated symptoms in a transgenic Caenorhabditis elegans AD model by decreasing Aβ oligomer levels.
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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".