Deciphering the Substrate Specificity of SbnA, the Enzyme Catalyzing the First Step in Staphyloferrin B Biosynthesis
Bibliographic record
Abstract
Staphylococcus aureus assembles the siderophore, staphyloferrin B, from l-2,3-diaminopropionic acid (l-Dap), α-ketoglutarate, and citrate. Recently, SbnA and SbnB were shown to produce l-Dap and α-ketoglutarate from O-phospho-l-serine (OPS) and l-glutamate. SbnA is a pyridoxal 5'-phosphate (PLP)-dependent enzyme with homology to O-acetyl-l-serine sulfhydrylases; however, SbnA utilizes OPS instead of O-acetyl-l-serine (OAS), and l-glutamate serves as a nitrogen donor instead of a sulfide. In this work, we examined how SbnA dictates substrate specificity for OPS and l-glutamate using a combination of X-ray crystallography, enzyme kinetics, and site-directed mutagenesis. Analysis of SbnA crystals incubated with OPS revealed the structure of the PLP-α-aminoacrylate intermediate. Formation of the intermediate induced closure of the active site pocket by narrowing the channel leading to the active site and forming a second substrate binding pocket that likely binds l-glutamate. Three active site residues were identified: Arg132, Tyr152, Ser185 that were essential for OPS recognition and turnover. The Y152F/S185G SbnA double mutant was completely inactive, and its crystal structure revealed that the mutations induced a closed form of the enzyme in the absence of the α-aminoacrylate intermediate. Lastly, l-cysteine was shown to be a competitive inhibitor of SbnA by forming a nonproductive external aldimine with the PLP cofactor. These results suggest a regulatory link between siderophore and l-cysteine biosynthesis, revealing a potential mechanism to reduce iron uptake under oxidative stress.
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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) | 0.000 | 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 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".