Influence of the Length and Charge on the Activity of α-Helical Amphipathic Antimicrobial Peptides
Bibliographic record
Abstract
Hydrophobic mismatch is important for pore-forming amphipathic antimicrobial peptides, as demonstrated recently [Grau-Campistany, A., et al. (2015) Sci. Rep. 5, 9388]. A series of different length peptides have been generated with the heptameric repeat sequence KIAGKIA, called KIA peptides, and it was found that only those helices sufficiently long to span the hydrophobic thickness of the membrane could induce leakage in lipid vesicles; there was also a clear length dependence of the antimicrobial and hemolytic activities. For the original KIA sequences, the cationic charge increased with peptide length. The goal of this work is to examine whether the charge also has an effect on activity; hence, we constructed two further series of peptides with a sequence similar to those of the KIA peptides, but with a constant charge of +7 for all lengths from 14 to 28 amino acids. For both of these new series, a clear length dependence similar to that of KIA peptides was observed, indicating that charge has only a minor influence. Both series also showed a distinct threshold length for peptides to be active, which correlates directly with the thickness of the membrane. Among the longer peptides, the new series showed activities only slightly lower than those of the original KIA peptides of the same length that had a higher charge. Shorter peptides, in which Gly was replaced with Lys, showed activities similar to those of KIA peptides of the same length, but peptides in which Ile was replaced with Lys lost their helicity and were less active.
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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 | 0.001 |
| 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 | 0.001 |
| 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".