A Novel Linear Amphipathic β-Sheet Cationic Antimicrobial Peptide with Enhanced Selectivity for Bacterial Lipids
Bibliographic record
Abstract
All known naturally occurring linear cationic peptides adopt an amphipathic alpha-helical conformation upon binding to lipids as an initial step in the induction of cell leakage. We designed an 18-residue peptide, (KIGAKI)3-NH2, that has no amphipathic character as an alpha-helix but can form a highly amphipathic beta-sheet. When bound to lipids, (KIGAKI)3-NH2 did indeed form a beta-sheet structure as evidenced by Fourier transform infrared and circular dichroism spectroscopy. The antimicrobial activity of this peptide was compared with that of (KIAGKIA)3-NH2, and it was better than that of GMASKAGAIAGKIAKVALKAL-NH2 (PGLa) and (KLAGLAK)3-NH2, all of which form amphipathic alpha-helices when bound to membranes. (KIGAKI)3-NH2 was much less effective at inducing leakage in lipid vesicles composed of mixtures of the acidic lipid, phosphatidylglycerol, and the neutral lipid, phosphatidylcholine, as compared with the other peptides. However, when phosphatidylethanolamine replaced phosphatidylcholine, the lytic potency of PGLa and the alpha-helical model peptides was reduced, whereas that of (KIGAKI)3-NH2 was improved. Fluorescence experiments using analogs containing a single tryptophan residue showed significant differences between (KIGAKI)3-NH2 and the alpha-helical peptides in their interactions with lipid vesicles. Because the data suggest enhanced selectivity between bacterial and mammalian lipids, linear amphipathic beta-sheet peptides such as (KIGAKI)3-NH2 warrant further investigation as potential antimicrobial 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) | 0.001 | 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".