A promising antibiotic candidate, brevinin-1 analogue 5R, against drug-resistant bacteria, with insights into its membrane-targeting mechanism
Bibliographic record
Abstract
In recent decades, antimicrobial peptides (AMPs) have held great promise as novel antibiotic agents. However, they have generally been excluded from clinical use due to certain limitations, such as poor biocompatibility and sensitivity to environmental conditions. In this study, we report a novel brevinin-1 type antimicrobial peptide B1LTe, derived from the skin secretion of Hylarana latouchii . Although the novel peptide B1LTe exhibited remarkable antimicrobial effects, its narrow therapeutic index (TI) can result in adverse drug reactions. Thus, the rational design by systematically scanning and replacing the inherent hydrophobic and cationic residues (Leucine and Lysine) with their D-enantiomeric counterparts was conducted to enhance the application potential of B1LTe. Simultaneously, we also applied lysine-to-arginine substitution within the modification. Among the derivates, 5 R demonstrated the highest selectivity and effectiveness against Methicillin-resistant Streptococcus aureus (MRSA), clinic-isolated Streptococcus pyogenes ( S. pyogenes ) strain, ranging from their planktonic to biofilm cells, both in vitro and in vivo. Furthermore, the remarkable adaptation of 5 R in saline and 20% serum indicates its potential for clinical application. We employed the in silico approach, which revealed the mechanism of interaction between 5 R and bacterial membranes. In addition, further mechanistic studies of 5 R elucidated the association between the collapsed proton motive force (PMF) and membrane perturbation as peptides aggregate on the bacterial membrane. Overall, our study suggests the D-enantiomeric 5 R can be a promising antibiotic agent against MDR bacteria in further clinical development and highlights the significance of cellular PMF as a potential target for the research of peptides' mode of action.
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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 | 0.001 |
| 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".