Activation of the SspA Serine Protease Zymogen of Staphylococcus aureus Proceeds through Unique Variations of a Trypsinogen-like Mechanism and Is Dependent on Both Autocatalytic and Metalloprotease-specific Processing
Bibliographic record
Abstract
The serine and cysteine proteases SspA and SspB of Staphylococcus aureus are secreted as inactive zymogens, zSspA and zSspB. Mature SspA is a trypsin-like glutamyl endopeptidase and is required to activate zSspB. Although a metalloprotease Aureolysin (Aur) is in turn thought to contribute to activation of zSspA, a specific role has not been demonstrated. We found that pre-zSspA is processed by signal peptidase at ANA(29) downward arrow, releasing a Leu(30) isoform that is first processed exclusively through autocatalytic intramolecular cleavage within a glutamine-rich propeptide segment, (40)QQTQSSKQQTPKIQ(53). The preferred site is Gln(43) with secondary processing at Gln(47) and Gln(53). This initial processing is necessary for optimal and subsequent Aur-dependent processing at Leu(58) and then Val(69) to release mature SspA. Although processing by Aur is rate-limiting in zSspA activation, the first active molecules of Val(69)SspA promote rapid intermolecular processing of remaining zSspA at Glu(65), producing an N-terminal (66)HANVILP isoform that is inactive until removal of the HAN tripeptide by Aur. Modeling indicated that His(66) of this penultimate isoform blocks the active site by hydrogen bonding to Ser(237) and occlusion of substrate. Binding of glutamate within the active site of zSspA is energetically unfavorable, but glutamine fits into the primary specificity pocket and is predicted to hydrogen bond to Thr(232) proximal to Ser(237), permitting autocatalytic cleavage of the glutamine-rich propeptide segment. These and other observations suggest that zSspA is activated through a trypsinogen-like mechanism where supplementary features of the propeptide must be sequentially processed in the correct order to allow efficient activation.
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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) | 0.001 | 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".