High-Throughput Screening Identifies Novel Inhibitors of the Acetyltransferase Activity of <i>Escherichia coli</i> GlmU
Bibliographic record
Abstract
The bifunctional GlmU protein catalyzes the formation of UDP-N-acetylglucosamine in a two-step reaction using the substrates glucosamine-1-phosphate, acetyl coenzyme A, and UTP. This metabolite is a common precursor to the synthesis of bacterial cell surface carbohydrate polymers, such as peptidoglycan, lipopolysaccharide, and wall teichoic acid that are involved in the maintenance of cell shape, permeability, and virulence. The C-terminal acetyltransferase domain of GlmU exhibits structural and mechanistic features unique to bacterial UDP-N-acetylglucosamine synthases, making it an excellent target for antibacterial design. In the work described here, we have developed an absorbance-based assay to screen diverse chemical libraries in high throughput for inhibitors to the acetyltransferase reaction of Escherichia coli GlmU. The primary screen of 50,000 drug-like small molecules identified 63 hits, 37 of which were specific to acetyltransferase activity of GlmU. Secondary screening and mode-of-inhibition studies identified potent inhibitors where compound binding within the acetyltransferase active site was requisite on the presence of glucosamine-1-phosphate and were competitive with the substrate acetyl coenzyme A. These molecules may represent novel chemical scaffolds for future antimicrobial drug discovery. In addition, this work outlines the utility of catalytic variants in targeting specific activities of bifunctional enzymes in high-throughput screens.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".