Adsorption of an Antimicrobial Peptide on Self-Assembled Monolayers by Molecular Dynamics Simulation
Bibliographic record
Abstract
We present results of molecular dynamics simulations of the interaction of a 48 amino acid peptide, carnobacteriocin B2, with model hydrophobic, anionic, and cationic self-assembled monolayers (SAMs). The model monolayers were formed by placing alkanethiols, HS-(CH(2))(10)-X, where the terminal functional group X was chosen to be CH(3), COO(-), or NH(3)(+). The carboxylate and amine groups were modeled as either fully charged or partially charged. Furthermore, simulations are presented for nanopatterned SAMs consisting of parallel stripes of hydrophobic/anionic and anionic/cationic SAMs. These simulations help elucidate the mechanisms of interaction of the peptide with model surfaces that emulate the chemical heterogeneity of lipid bilayer membranes or peptide nanoarrays. The simulation results depict how the nanoscale chemical heterogeneity of surfaces can simultaneously alter the peptide's interaction with the surface and its secondary structure. Hydrophobic interactions result in the strongest adsorption of the peptide to the monolayer, simultaneously maintaining the structural integrity of the peptide. Electrostatic interactions, on the other hand, tend to enhance the solvation of the peptide, thereby causing radical changes in the secondary structure.
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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".