Hydrophobicity and helicity of membrane‐interactive peptides containing peptoid residues
Bibliographic record
Abstract
Peptoid (N-alkylglycyl) residues in peptides have been studied in a variety of applications, but their behavior in membrane environments has not been systematically investigated. We have synthesized a series of membrane-interactive peptides of prototypic structure KKAAAXAAAAAXAAWAAXAAAKKKK-amide, where X corresponds to the peptoid residues Nala (= sarcosine), Nval, Nile, Nleu, Nphe, and Ntrp. Investigation of their relative hydrophobic character by high-performance liquid chromatography indicated an order of hydrophobicity Ntrp > Nphe > Nleu > Nile > Nval > Nala-largely parallel to the relative scale for these side-chains in natural amino acids, although all values were significantly more "hydrophilic" than their amino acid correspondents. Conformations of peptoid-containing peptides measured by circular dichroism spectroscopy were unordered in the presence of SDS micelles but helical for peptides with X = the corresponding amino acids, suggesting a general helix-breaking tendency for the peptoid residues. However, peptides were able to form helical structures in the solvent n-butanol, indicating that this conformation is possible if peptides became inserted into micellar phases. The latter notion was confirmed by increasing hydrophobic content of the peptides by embedding peptoid Nala residues in Leu-rich rather than Ala-rich sequences, which promoted peptide insertion and helical structure in micelles. The overall results suggest that judicious interspersing of amino acid and peptoid residues in peptide sequences can produce hydrophobic water-soluble materials with membrane-partitioning capacity.
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) | 0.000 | 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".