Effects of net charge and the number of positively charged residues on the biological activity of amphipathic α‐helical cationic antimicrobial peptides
Bibliographic record
Abstract
Abstract In our previous study, we utilized a 26‐residue amphipathic α‐helical antimicrobial peptide L‐V13K (Chen et al., Antimicrob Agents Chemother 2007, 51, 1398–1406) as the framework to study the effects of peptide hydrophobicity on the mechanism of its antimicrobial action. In this study, we explored the effects of net charge and the number of positively charged residues on the hydrophilic/polar face of L‐V13K on its biological activity (antimicrobial and hemolytic) and biophysical properties (hydrophobicity, amphipathicity, helicity, and peptide self‐association). The net charge of V13K analogs at pH 7 varied between −5 and +10 and the number of positively charged residues varied from 1 to 10. The minimal inhibitory concentrations (MIC) against six strains of Pseudomonas aeruginosa as well as other gram‐negative and gram‐positive bacteria were determined along with the maximal peptide concentration that produces no hemolysis of human red blood cells (MHC). Our results show that the number of positively charged residues on the polar face and net charge are both important for both antimicrobial activity and hemolytic activity. The most dramatic observation is the sharp transition of hemolytic activity on increasing one positive charge on the polar face of V13K i.e., the change from +8 to +9 resulted in greater than 32‐fold increase in hemolytic activity (250 μg/ml to <7.8 μg/ml, respectively). © 2007 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 90: 369–383, 2008. This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com
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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".