Interactions of the designed antimicrobial peptide MB21 and truncated dermaseptin S3 with lipid bilayers: molecular-dynamics simulations
Bibliographic record
Abstract
Molecular-dynamics simulations covering 30 ns of both a natural and a synthetic antimicrobial peptide in the presence of a zwitterionic lipid bilayer were performed. In both simulations, copies of the peptides were placed in an alpha-helical conformation on either side of the bilayer about 10 A (1 A=0.1 nm) from the interface, with either the hydrophobic or the positively charged face of the helix directed toward the bilayer surface. The degree of peptide-lipid interaction was dependent on the starting configuration: surface binding and subsequent penetration of the bilayer was observed for the hydrophobically oriented peptides, while the charge-oriented peptides demonstrated at most partial surface binding. Aromatic residues near the N-termini of the peptides appear to play an important role in driving peptide-lipid interactions. A correlation between the extent of peptide-lipid interactions and helical stability was observed in the simulations. Insertion of the peptides into the bilayer caused a dramatic increase in the lateral area per lipid and decrease in the bilayer thickness, resulting in substantial disordering of the lipid chains. Results from the simulations are consistent with early stages of proposed mechanisms for the lytic activity of antimicrobial peptides. In addition to these 'free' simulations, 25 ns simulations were carried out with the peptides constrained at three different distances relative to the bilayer interface. The constraint forces are in agreement with the extent of peptide-bilayer insertion observed in the free simulations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".