Revisiting Peptide Amphiphilicity for Membrane Pore Formation
Bibliographic record
Abstract
It has previously been shown that an amphipathic de novo designed peptide made of 10 leucines and four phenylalanines substituted with crown ethers induces vesicle leakage without selectivity. To gain selectivity against negatively charged dimyristoylphosphatidylglycerol (DMPG) bilayers, one or two leucines of the peptide were substituted with positively charged residues at each position. All peptides induce significant calcein leakage of DMPG vesicles. However, some peptides do not induce significant leakage of zwitterionic dimyristoylphosphatidylcholine vesicles and are thus active against only bacterial model membranes. The intravesicular leakage is induced by pore formation instead of membrane micellization. Nonselective peptides are mostly helical, while selective peptides mainly adopt an intermolecular β-sheet structure. This study therefore demonstrates that the position of the lysine residues significantly influences the secondary structure and bilayer selectivity of an amphipathic 14-mer peptide, with β-sheet peptides being more selective than helical peptides.
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".