Bactericidal efficiency and mechanism of specifically targeted antimicrobial peptides optimized based on structural and functional relationships
Bibliographic record
Abstract
Abstract In contrast to traditional broad-spectrum antibiotics, it is difficult for bacteria to develop resistance to most specifically targeted antimicrobial peptides (STAMPs), moreover, they can maintain a normal ecological balance and provide long-term protection for the body. However, therapeutic applications of STAMPS are hindered by their weak activity, and imperfect specificity as well as lack of knowledge to understand their structure-activity relationships. To further investigate the effects of different parameters on the biological activities of STAMPs, a peptide sequence, WKKIWK D PGIKKWIK, was truncated, extended, and provided with an increased charge and altered amphipathicity. In addition, a novel template modification method was introduced, in which a phage-displayed peptide that recognized and bound to E. coli cells was attached at the end of the sequence. Compared with the traditional template modification method, peptide 11, which contained a phage-displayed peptide at the C-terminus, exhibited superior narrow-spectrum antibacterial activity against E. coli compared to that of parental peptide 2, and the activity and specificity of 11 were increased by 5.0 and 2.4 times, respectively. Additionally, 11 showed low cell toxicity and relatively desirable salt, serum, acid and alkaline stability. In this study, 11 specifically killed E. coli by causing cytoplasmic membrane rupture and cytosol leakage. In summary, these findings are useful for improving the activity and specificity of STAMPs and show that peptide 11 is better able to combat the growing threat of E. coli infections.
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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".