Substrate Specificity of the Streptococcal Cysteine Protease
Bibliographic record
Abstract
The streptococcal pyrogenic exotoxin B (SpeB) is an important factor in mediating Streptococcus pyogenes infections. SpeB is the zymogen of the streptococcal cysteine protease (SCP), of which relatively little is known regarding substrate specificity. To investigate this aspect of SCP function, a series of internally quenched fluorescent substrates was designed based on the cleavage sites identified in the autocatalytic processing of SpeB to mature SCP. The best substrates for SCP contain three amino acids in the nonprimed position (i.e. AIK in P(3)-P(2)-P(1)). Varying the length of the substrate on the primed side of the scissile bond has a relatively lower effect on activity. The highest activity (k(cat)/K(M) = 2.8 +/- 0.6 (10(5) x m(-1)s(-1)) is observed for the pentamer 3-aminobenzoic acid-AIKAG-3-nitrotyrosine, which spans subsites S(3) to S(2)' on the enzyme. High pressure liquid chromatography and mass spectrometry analyses show that the substrates are cleaved at the site predicted from the autoprocessing experiments. These results show that SCP can display an important level of endopeptidase activity. Substitutions at position P(2) of the substrate clearly indicate that the S(2) subsite of SCP can readily accommodate substrates containing a hydrophobic residue at that position and that some topological preference exists for that subsite. Substitutions in positions P(3), P(1), and P(1)' had little or no effect on SCP activity. The substrate specificity outlined in this work further supports the similarity between SCP and the cysteine proteases of the papain family. From the data regarding the identified or proposed natural substrates for SCP, it appears that this substrate specificity profile may also apply to the processing of mammalian and streptococcal protein targets by SCP.
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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 | 0.001 |
| 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".