Dioctanoyl Ultrashort Tetrabasic β-Peptides Sensitize Multidrug-Resistant Gram-Negative Bacteria to Novobiocin and Rifampicin
Bibliographic record
Abstract
Recently reported peptidomimetics with increased resistance to trypsin were shown to sensitize priority multidrug-resistant (MDR) Gram-negative bacteria to novobiocin and rifampicin. To further optimize proteolytic stability, β-amino acid-containing derivatives of these compounds were prepared, resulting in three dioctanoyl ultrashort tetrabasic β-peptides (dUSTBβPs). The nonhemolytic dUSTBβP 3, comprised of three β 3 -homoarginine residues and two fatty acyl tails eight carbons long, enhanced the antibacterial activity of various antibiotics from different classes. Notably, compound 3 retained the ability to potentiate novobiocin and rifampicin in wild-type Gram-negative bacteria against MDR clinical isolates of Pseudomonas aeruginosa , Acinetobacter baumannii , Escherichia coli , Klebsiella pneumoniae , and Enterobacter cloacae . dUSTBβP 3 reduced the minimum inhibitory concentration of novobiocin and rifampicin below their interpretative susceptibility breakpoints. Furthermore, compound 3 exhibited improved in vitro stability (86.8 ± 3.7% remaining) relative to its α-amino acid-based counterpart (39.5 ± 7.4% remaining) after a 2 h incubation in human plasma.
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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".