Processing of predicted substrates of fungal Kex2 proteinases from Candida albicans, C. glabrata, Saccharomyces cerevisiae and Pichia pastoris
Bibliographic record
Abstract
BACKGROUND: Kexin-like proteinases are a subfamily of the subtilisin-like serine proteinases with multiple regulatory functions in eukaryotes. In the yeast Saccharomyces cerevisiae the Kex2 protein is biochemically well investigated, however, with the exception of a few well known proteins such as the alpha-pheromone precursors, killer toxin precursors and aspartic proteinase propeptides, very few substrates are known. Fungal kex2 deletion mutants display pleiotropic phenotypes that are thought to result from the failure to proteolytically activate such substrates. RESULTS: In this study we have aimed at providing an improved assembly of Kex2 target proteins to explain the phenotypes observed in fungal kex2 deletion mutants by in vitro digestion of recombinant substrates from Candida albicans and C. glabrata. We identified CaEce1, CA0365, one member of the Pry protein family and CaOps4-homolog proteins as novel Kex2 substrates. CONCLUSION: Statistical analysis of the cleavage sites revealed extended subsite recognition of negatively charged residues in the P1', P2' and P4' positions, which is also reflected in construction of the respective binding pockets in the ScKex2 enzyme. Additionally, we provide evidence for the existence of structural constrains in potential substrates prohibiting proteolysis. Furthermore, by using purified Kex2 proteinases from S. cerevisiae, P. pastoris, C. albicans and C. glabrata, we show that while the substrate specificity is generally conserved between organisms, the proteinases are still distinct from each other and are likely to have additional unique substrate recognition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".