Discrimination of Differentially Inhibited Cysteine Proteases by Activity-Based Profiling Using Cystatin Variants with Tailored Specificities
Bibliographic record
Abstract
Recent research has shown the possibility of tailoring the inhibitory specificity of plant cystatins toward cysteine (Cys) proteases by single mutations at positively selected amino acid sites. Here we devised a cystatin activity-based profiling approach to assess the impact of such mutations at the proteome scale using single variants of tomato cystatin SlCYS8 and digestive Cys proteases of the herbivorous insect, Colorado potato beetle, as a model. Biotinylated forms of SlCYS8 and SlCYS8 variants were used to capture susceptible Cys proteases in insect midgut protein extracts by biotin immobilization on avidin-embedded beads. A quantitative LC-MS/MS analysis of the captured proteins was performed to compare the inhibitory profile of different SlCYS8 variants. The approach confirmed the relevance of phylogenetic inferences categorizing the insect digestive Cys proteases into six functionally distinct families. It also revealed significant variation in protease family profiles captured with N-terminal variants of SlCYS8, in line with in silico structural models for Cys protease-SlCYS8 interactions suggesting a functional role for the N-terminal region. Our data confirm overall the usefulness of cystatin activity-based protease profiling for the monitoring of Cys protease-inhibitor interactions in complex biological systems. They also illustrate the potential of biotinylated cystatins to identify recombinant cystatin candidates for the inactivation of specific Cys protease targets.
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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) | 0.000 | 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".