Stapling strategy for slowing helicity interconversion of α-helical peptides and isolating chiral auxiliary-free one-handed forms
Bibliographic record
Abstract
Abstract In nature, α-helical peptides adopt right-handed conformations that are dictated by L-amino acids. Isolating one-handed α-helical peptides composed of only achiral components remains a significant challenge. Here, this goal is achieved by optical resolution of the corresponding racemic (quasi-)static α-helical peptide with double stapling, which effectively freezes the interconversion between the right-handed (P)- and left-handed (M)-α-helices. An as-obtained doubly stapled analogue having an unprotected L-valine residue at the C-terminus transforms from a kinetically trapped (M)-α-helix to a thermodynamically stable (P)-α-helix upon heating. In contrast, the corresponding singly stapled α-helical peptide undergoes an acid/base-triggered and solvent-induced reversible inversion of its preferred helicity within minutes. The interconversion rates of the singly and doubly stapled α-helical peptide foldamers are approximately 106 and 1012 times slower, respectively, than that of a non-stapled dynamic helical peptide. Therefore, the enantiopure doubly-stapled (quasi-)static α-helical peptide would retain its optical activity for several years at 25 °C.
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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".