Conjugation of Aurein 2.2 to HPG Yields an Antimicrobial with Better Properties
Bibliographic record
Abstract
Aurein 2.2 is an antimicrobial peptide (AMP) whose mechanism of action is quite well-understood and that has good activity against Gram-positive bacteria. It is, however, highly cytotoxic. Poly(ethylene glycol) (PEG) conjugation (PEGylation) of protein and peptide drugs has been used for decades to improve their in vivo efficacy and blood circulation by enhancing the biocompatibility of the protein or peptide in question. However, the relatively large hydrodynamic size, high intrinsic viscosity, the limited number of functional groups available for conjugation, and immunogenicity of high molecular weight PEG limits its use in bioconjugation applications. Recently, hyperbranched polyglycerol (HPG) has been gaining attention as an alternative to PEG due to its excellent biocompatibility. Here, for the first time, we report the synthesis of HPG conjugates of antimicrobial peptides. Aurein 2.2 peptide was conjugated to high molecular weight HPG with a varying number of peptides per polymer, and the biocompatibility and antimicrobial activity of the conjugates were investigated. The antimicrobial activity of the peptide and its conjugates were determined by measuring the minimal inhibitory concentration (MIC) against Staphylococcus aureus and Staphylococcus epidermidis. The interaction of aurein 2.2 peptide and the conjugates with a model bacterial biomembrane was investigated using CD spectroscopy to understand the mode of action of the conjugates. The biocompatibility of the AMP-polymer conjugates was investigated by measuring red cell lysis, platelet activation and aggregation, complement activation, blood coagulation, and cell toxicity. Our results show that the size of the conjugates and the peptide density influence the biocompatibility of the antimicrobial conjugates. These results will help to further define the properties of HPG-AMP conjugates and set the stage for development of better therapeutic agents.
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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".