Important structural features of 15-residue lactoferricin derivatives and methods for improvement of antimicrobial activity
Bibliographic record
Abstract
This review focuses on important structural features affecting the antimicrobial activity of 15-residue derivatives of lactoferricins. Our investigations are based on an alanine-scan of a 15-residue bovine lactoferricin derivative that revealed the absolute necessity of two tryptophan residues for antimicrobial activity. This "tryptophan-effect" was further explored in homologous derivatives of human, caprine, and porcine lactoferricins by the incorporation of one additional tryptophan residue, and by increasing the content of tryptophan in the bovine derivative to five residues. Most of the resulting peptides display a substantial increase in antimicrobial activity. To identify which molecular properties make tryptophan so effective, a series of bovine lactoferricin derivatives were prepared containing non-encoded unnatural aromatic amino acids, which represented various aspects of the physicochemical nature of tryptophan. The results clearly demonstrate that tryptophan is not unique since most of the modified peptides were of higher antimicrobial potency than the native peptide. The size and three-dimensional shape of the inserted "super-tryptophans" are the most important determinants for the high antimicrobial activity of the modified peptides. This review also describes the use of a "soft-modeling" approach in order to identify important structural parameters affecting the antimicrobial activity of modified 15-residue murine lactoferricin derivatives. This QSAR-study revealed that the net charge, charge asymmetry, and micelle affinity of the peptides were the most important structural parameters affecting their antimicrobial activity.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".