Radical Formation Initiates Solvent-Dependent Unfolding and β-sheet Formation in a Model Helical Peptide
Bibliographic record
Abstract
We examined the effects of Cα-centered radical formation on the stability of a model helical peptide, N-Ac-KK(AL)10KK-NH2. Three, 100 ns molecular dynamics simulations using the OPLS-AA force field were carried out on each α-helical peptide in six distinct binary TIP4P water/2,2,2-trifluoroethanol (TFE) mixtures. The α-helicity was at a maximum in 20% TFE, which was inversely proportional to the number of H-bonds between water molecules and the peptide backbone. The radial distribution of TFE around the peptide backbone was highest in 20% TFE, which enhanced helix stability. The Cα-centered radical initiated the formation of a turn within 5 ns, which was a smaller kink at high TFE concentrations, and a loop at lower TFE concentrations. The highest helicity of the peptide radical was measured in 100% TFE. The formation of hydrogen bonds between the peptide backbone and water destabilized the helix, whereas the clustering of TFE molecules around the radical center stabilized the helix. Following radical termination, the once helical structure converted to a β-sheet rich state in 100% water only, and this transition did not occur in the nonradical control peptide. This study gives evidence on how the formation of peptide radicals can initiate α-helical to β-sheet transitions under oxidative stress conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".