Comparison of Biophysical and Biologic Properties of <i>α</i>‐Helical Enantiomeric Antimicrobial Peptides
Bibliographic record
Abstract
In our previous study (Chen et al. J Biol Chem 2005, 280:12316-12329), we utilized an alpha-helical antimicrobial peptide V(681) as the framework to study the effects of peptide hydrophobicity, amphipathicity, and helicity on biologic activities where we obtained several V(681) analogs with dramatic improvement in peptide therapeutic indices against gram-negative and gram-positive bacteria. In the present study, the D-enantiomers of three peptides--V(681), V13A(D) and V13K(L) were synthesized to compare biophysical and biologic properties with their enantiomeric isomers. Each D-enantiomer was shown by circular dichroism spectroscopy to be a mirror image of the corresponding L-isomer in benign conditions and in the presence of 50% trifluoroethanol. L- and D-enantiomers exhibited equivalent antimicrobial activities against a diverse group of Pseudomonas aeruginosa clinical isolates, various gram-negative and gram-positive bacteria and a fungus. In addition, L- and D-enantiomeric peptides were equally active in their ability to lyse human red blood cells. The similar activity of L- and D-enantiomeric peptides on prokaryotic or eukaryotic cell membranes suggests that there are no chiral receptors and the cell membrane is the sole target for these peptides. Peptide D-V13K(D) showed significant improvements in the therapeutic indices compared with the parent peptide V(681) by 53-fold against P. aeruginosa strains, 80-fold against gram-negative bacteria, 69-fold against gram-positive bacteria, and 33-fold against Candida albicans. The excellent stability of D-enantiomers to trypsin digestion (no proteolysis by trypsin) compared with the rapid breakdown of the L-enantiomers highlights the advantage of the D-enantiomers and their potential as clinical therapeutics.
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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) | 0.000 | 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 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".