Dual functionality of β-tryptase protomers as both proteases and cofactors in the active tetramer
Bibliographic record
Abstract
Human β-tryptase, a tetrameric trypsin-like serine protease, is an important mediator of the allergic inflammatory responses in asthma. During acute hypersensitivity reactions, mast cells degranulate, releasing active tetramer as a complex with proteoglycans. Extensive efforts have focused on developing therapeutic β-tryptase inhibitors, but its unique activation mechanism is less well-explored. Tryptase is active only after proteolytic removal of the pro-domain followed by tetramer formation via two distinct symmetry-related interfaces. We show that the cleaved I16G mutant cannot tetramerize, likely due to impaired insertion of its N terminus into its "activation pocket," indicating allosteric linkage at multiple sites on each protomer. We engineered cysteines into each of the two distinct interfaces (Y75C for small or I99C for large) to assess the activity of each tetramer and disulfide-locked dimer. Using size-exclusion chromatography and enzymatic assays, we demonstrate that the two large tetramer interfaces regulate enzymatic activity, elucidating the importance of this protein-protein interaction for allosteric regulation. Notably, the I99C large interface dimer is active, even in the absence of heparin. We show that a monomeric β-tryptase mutant (I99C*/Y75A/Y37bA, where C* is cysteinylated Cys-99) cannot form a dimer or tetramer, yet it is active but only in the presence of heparin. Thus heparin both stabilizes the tetramer and allosterically conditions the active site. We hypothesize that each β-tryptase protomer in the tetramer has two distinct roles, acting both as a protease and as a cofactor for its neighboring protomer, to allosterically regulate enzymatic activity, providing a rationale for direct correlation of tetramer stability with proteolytic activity.
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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 | 0.001 |
| 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".