Amphiphilicity Is a Key Determinant in the Membrane Interactions of Synthetic 14-mer Cationic Peptide Analogues
Bibliographic record
Abstract
Cationic antimicrobial peptides are a component of the innate immune system of several organisms and represent an interesting alternative to fight multiresistant bacteria. In this context, we have elaborated a synthetic peptide scaffold allowing the study of the impact of different molecular determinants on the membrane interactions. The aim of the present study was to elucidate the mechanism of action of two cationic peptides that derive from a neutral 14-mer template peptide and where the hydrophilic portion is composed of a crown ether. The R5R10 peptide is active in the presence of both negatively charged and zwitterionic membranes (nonselective) and adopts an α-helical conformation, whereas the R4R11 peptide is more active in the presence of negatively charged membranes (selective) and forms intermolecular β-sheet structures. Both the membrane topology and the location of the peptides have been assessed using solid-state NMR and attenuated total reflectance Fourier transform infrared spectroscopy. In addition, fluorescence experiments have been performed on different membrane mixtures to evaluate the ability of the peptides to induce a positive curvature to the membrane. Overall, for both the R5R10 and R4R11 peptides, the results are consistent with a mechanism of action similar to the sinking-raft model in which the peptides are mainly lying flat on the membrane surface and impose a bending stress to the membrane, thus leading to the formation of pores. Furthermore, the difference of membrane selectivity between R5R10 and R4R11 peptides is due to their differing amphipathic properties which modulate the membrane activity on zwitterionic model membranes.
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".