A Small-Molecule Screening Platform for the Discovery of Inhibitors of Undecaprenyl Diphosphate Synthase
Bibliographic record
Abstract
The bacterial cell wall has long been a celebrated target for antibacterial drug discovery due to its critical nature in bacteria and absence in mammalian systems. At the heart of the cell wall biosynthetic pathway lies undecaprenyl phosphate (Und-P), the lipid-linked carrier upon which the bacterial cell wall is built. This study exploits recent insights into the link between late-stage wall teichoic acid inhibition and Und-P production, in Gram-positive organisms, to develop a cell-based small-molecule screening platform that enriches for inhibitors of undecaprenyl diphosphate synthase (UppS). Screening a chemical collection of 142,000 small molecules resulted in the identification of 6 new inhibitors of UppS. To date, inhibitors of UppS have generally shown off-target effects on membrane potential due to their physical-chemical characteristics. We demonstrate that MAC-0547630, one of the six inhibitors identified, exhibits selective, nanomolar inhibition against UppS without off-target effects on membrane potential. Such characteristics make it a unique chemical probe for exploring the inhibition of UppS in bacterial cell systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".