Structure and Mechanism of Staphylococcus aureus TarS, the Wall Teichoic Acid β-glycosyltransferase Involved in Methicillin Resistance
Bibliographic record
Abstract
In recent years, there has been a growing interest in teichoic acids as targets for antibiotic drug design against major clinical pathogens such as Staphylococcus aureus, reflecting the disquieting increase in antibiotic resistance and the historical success of bacterial cell wall components as drug targets. It is now becoming clear that β-O-GlcNAcylation of S. aureus wall teichoic acids plays a major role in both pathogenicity and antibiotic resistance. Here we present the first structure of S. aureus TarS, the enzyme responsible for polyribitol phosphate β-O-GlcNAcylation. Using a divide and conquer strategy, we obtained crystal structures of various TarS constructs, mapping high resolution overlapping N-terminal and C-terminal structures onto a lower resolution full-length structure that resulted in a high resolution view of the entire enzyme. Using the N-terminal structure that encapsulates the catalytic domain, we furthermore captured several snapshots of TarS, including the native structure, the UDP-GlcNAc donor complex, and the UDP product complex. These structures along with structure-guided mutants allowed us to elucidate various catalytic features and identify key active site residues and catalytic loop rearrangements that provide a valuable platform for anti-MRSA drug design. We furthermore observed for the first time the presence of a trimerization domain composed of stacked carbohydrate binding modules, commonly observed in starch active enzymes, but adapted here for a poly sugar-phosphate glycosyltransferase.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".