Opposing effects of cationic antimicrobial peptides and divalent cations on bacterial lipopolysaccharides
Bibliographic record
Abstract
The permeability of the bacterial outer membrane, enclosing Gram-negative bacteria, depends on the interactions of the outer, lipopolysaccharide (LPS) layer, with surrounding ions and molecules. We present a coarse-grained model for describing how cationic amphiphilic molecules (e.g., antimicrobial peptides) interact with and perturb the LPS layer in a biologically relevant medium, containing monovalent and divalent salt ions (e.g., Mg^{2+}). In our approach, peptide binding is driven by electrostatic and hydrophobic interactions and is assumed to expand the LPS layer, eventually priming it for disruption. Our results suggest that in parameter ranges of biological relevance (e.g., at micromolar concentrations) the antimicrobial peptide magainin 2 effectively disrupts the LPS layer, even though it has to compete with Mg^{2+} for the layer. They also show how the integrity of LPS is restored with an increasing concentration of Mg^{2+}. Using the approach, we make a number of predictions relevant for optimizing peptide parameters against Gram-negative bacteria and for understanding bacterial strategies to develop resistance against cationic 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".