Rapid autocatalytic activation of the M4 metalloprotease aureolysin is controlled by a conserved N‐terminal fungalysin‐thermolysin‐propeptide domain
Bibliographic record
Abstract
SUMMARY: The Staphylococcus aureus proteolytic cascade consists of a metalloprotease aureolysin (Aur), which activates a serine protease zymogen proSspA, which in turn activates the SspB cysteine protease. As with other M4 metalloproteases, including elastase of Pseudomonas aeruginosa, the propeptide of proAur contains an N-terminal fungalysin-thermolysin-propeptide (FTP) domain. Autocatalytic activation of proAur was initiated by processing at T85 downward arrowL(86) in the FTP domain. This differed from the mechanism described for proElastase, where the FTP domain has an RY motif in place of TL(86), and processing occurred at the junction of the propeptide and metalloprotease domains, which remained as an inactive complex during passage across the outer membrane. When TL(86) in the FTP domain was replaced with RY, an intact N-terminal propeptide was secreted, but the M4 metalloprotease domain was degraded. Consequently, this segment of the FTP domain promotes intramolecular processing of proAur while bestowing a chaperone function, but discourages processing within the FTP domain of proElastase, where activation must be co-ordinated with passage across a second membrane. We conclude that the FTP domain of proAur is adapted to facilitate a rapid autocatalytic activation mechanism, consistent with the role or proAur as initiator of the staphylococcal proteolytic cascade.
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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 | 0.000 |
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".