Basis for Selectivity of Cationic Antimicrobial Peptides for Bacterial Versus Mammalian Membranes
Bibliographic record
Abstract
Novel cationic antimicrobial peptides typified by structures such as KKKKKKAAXAAWAAXAA-NH2, where X = Phe/Trp, and several of their analogues display high activity against a variety of bacteria but exhibit no hemolytic activity even at high dose levels in mammalian erythrocytes. To elucidate their mechanism of action and source of selectivity for bacterial membranes, phospholipid mixtures mimicking the compositions of natural bacterial membranes (containing anionic lipids) and mammalian membranes (containing zwitterionic lipids + cholesterol) were challenged with the peptides. We found that peptides readily inserted into bacterial lipid mixtures, although no insertion was detected in model "mammalian" membranes. The depth of peptide insertion into model bacterial membranes was estimated by Trp fluorescence quenching using doxyl groups variably positioned along the phospholipid acyl chains. Peptide antimicrobial activity generally increased with increasing depth of peptide insertion. The overall results, in conjunction with molecular modeling, support an initial electrostatic interaction step in which bacterial membranes attract and bind peptide dimers onto the bacterial surface, followed by the "sinking" of the hydrophobic core segment to a peptide sequence-dependent depth of approximately 2.5-8 A into the membrane, largely parallel to the membrane surface. Antimicrobial activity was likely enhanced by the fact that the peptide sequences contain AXXXA sequence motifs, which promote their dimerization, and possibly higher oligomerization, as assessed by SDS-polyacrylamide gel analysis and fluorescence resonance energy transfer experiments. The high selectivity of these peptides for nonmammalian membranes, combined with their activity toward a wide spectrum of Gram-negative and Gram-positive bacteria and yeast, while retaining water solubility, represent significant advantages of this class of peptides.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".