Small Polar Hits against <i>S. aureus</i>: Screening, Initial Hit Optimization, and Metabolomic Studies
Bibliographic record
Abstract
Abstract The global prevalence of antibacterial resistance requires new antibacterial drugs with novel chemical scaffolds and modes of action. It is also vital to design compounds with optimal physicochemical properties to permeate the bacterial cell envelope. We described an approach of combining and integrating whole cell screening and metabolomics into early antibacterial drug discovery using a library of small polar compounds. Whole cell screening of a diverse library of small polar compounds against Staphylococcus aureus gave compound 2. Hit expansion was carried out to determine structure–activity relationships. A selection of compounds from this series, together with other screened active compounds, was subjected to an initial metabolomics study to provide a metabolic fingerprint of the mode of action. It was found that compound 2 and its analogues have a different mode of action from some of the known antibacterial compounds tested. This early study highlighted the potential of whole cell screening and metabolomics in early antibacterial drug discovery. Future works will require improving potency and performing orthogonal studies to confirm the modes 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".