Antimicrobial Peptide–Polymer Conjugates with High Activity: Influence of Polymer Molecular Weight and Peptide Sequence on Antimicrobial Activity, Proteolysis, and Biocompatibility
Bibliographic record
Abstract
We report the synthesis, characterization, activity, and biocompatibility of a novel series of antimicrobial peptide-polymer conjugates. Using parent peptide aurein 2.2, we designed a peptide array (∼100 peptides) with single and multiple W and R mutations and identified antimicrobial peptides (AMPs) with potent activity against Staphylococcus aureus (S. aureus). These novel AMPs were conjugated to hyperbranched polyglycerols (HPGs) of different molecular weights and number of peptides to improve their antimicrobial activity and toxicity. The cell and blood compatibility studies of these conjugates demonstrated better properties than those of the AMP alone. However, conjugates showed lower antimicrobial activity in comparison to that of peptides, as determined from minimal inhibition concentrations (MICs) against S. aureus, but considerably better than that of the available polymer-AMP conjugates in the literature. In addition to measuring MICs and characterizing the biocompatibility, circular dichroism spectroscopy was used to investigate the interaction of the novel conjugates with model bacterial biomembranes. Moreover, the novel conjugates were exposed to trypsin to evaluate their stability. It was found that the conjugates resist proteolysis in comparison with unprotected peptides. The peptide conjugates were active in serum and whole blood. Overall, the results show that combining a highly active AMP and low-molecular-weight HPG yields bioconjugates with excellent biocompatibility, MICs below 100 μg/mL, and proteolytic stability, which could potentially improve its utility for in vivo applications.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".