Improving the Activity of Trp-Rich Antimicrobial Peptides by Arg/Lys Substitutions and Changing the Length of Cationic Residues
Bibliographic record
Abstract
Antimicrobial peptides (AMPs) constitute a promising alternative for the development of new antibiotics that could potentially counteract the growing number of antibiotic-resistant bacteria. However, the AMP structure–function relationships remain unclear and detailed studies are still necessary. The positively charged amino acid residues (Arg and Lys) play a crucial role in the activity of most AMPs due to the promotion of electrostatic interactions between the peptides and bacterial membranes. In this work we have analyzed the antimicrobial and structural properties of several Trp-rich AMPs containing exclusively either Arg or Lys as the positively charged residues. Their antimicrobial activity and mechanism of action were investigated, showing that Lys residues give rise to a reduced antimicrobial potency for most peptides, which was correlated, in turn, with a decrease in their ability to permeabilize the cytoplasmic membrane of Escherichia coli. Additionally, the presence of Arg and Lys renders the peptides susceptible to degradation by proteases, such as trypsin, limiting their therapeutic use. Therefore, modifications of the side chain length of Arg and Lys were investigated in an attempt to improve the protease resistance of AMPs. This approach resulted in enhanced stability to trypsin digestion, and in several cases, shorter sidechains conserved or even improved the antimicrobial activity. All together, these results suggest that Arg-to-Lys substitutions, coupled with side chain length modifications, can be extremely useful for improving the activity and stability of AMPs.
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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 | 0.000 |
| 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) | 0.001 | 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".