Design, Synthesis, and Evaluation of New 1H-Benzo[d]imidazole Based PqsR Inhibitors as Adjuvant Therapy for Pseudomonas aeruginosa Infections
Bibliographic record
Abstract
Pseudomonas aeruginosa is one of the top priority pathogens that requires immediate attention according to the World Health Organisation (WHO). Due to the alarming shortage of novel antimicrobials, targeting quorum sensing (QS), a bacterial cell to cell signaling system controlling virulence, has emerged as a promising approach as an antibiotic adjuvant therapy. Interference with the pqs system, one of three QS systems in P. aeruginosa, results in reduction of bacterial virulence gene expression and biofilm maturation. Herein, we report a hit to lead process to fine-tune the potency of our previously reported inhibitor 1 (IC50 3.2 μM in P. aeruginosa PAO1-L), which led to the discovery of 2-(4-(3-((6-chloro-1-isopropyl-1H-benzo[d]imidazol-2-yl)amino)-2-hydroxypropoxy)phenyl)acetonitrile (6f) as a potent PqsR antagonist. Compound 6f inhibited the PqsR-controlled PpqsA-lux transcriptional reporter fusion in P. aeruginosa at low submicromolar concentrations. Moreover, 6f showed improved efficacy against P. aeruginosa CF isolates with significant inhibition of pyocyanin, 2-alkyl-4(1H)-quinolones production.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".