Family-wide characterization of matrix metalloproteinases from <i>Arabidopsis thaliana</i> reveals their distinct proteolytic activity and cleavage site specificity
Bibliographic record
Abstract
MMPs (matrix metalloproteases) are a family of zinc-dependent endopeptidases widely distributed throughout all kingdoms of life. In mammals, MMPs play key roles in many physiological and pathological processes, including remodelling of the extracellular matrix. In the genome of the annual plant Arabidopsis thaliana, five MMP-like proteins (At-MMPs) are encoded, but their function is unknown. Previous work on these enzymes was limited to gene expression analysis, and so far proteolytic activity has been shown only for At1-MMP. We expressed and purified the catalytic domains of all five At-MMPs as His-tagged proteins in Escherichia coli cells to delineate the biochemical differences and similarities among the Arabidopsis MMP family members. We demonstrate that all five recombinant At-MMPs are active proteases with distinct preferences for different protease substrates. Furthermore, we performed a family-wide characterization of their biochemical properties and highlight similarities and differences in their cleavage site specificities as well as pH- and temperature-dependent activities. Detailed analysis of their sequence specificity using PICS (proteomic identification of protease cleavage sites) revealed profiles similar to human MMPs with the exception of At5-MMP; homology models of the At-MMP catalytic domains supported these results. Our results suggest that each At-MMP may be involved in different proteolytic processes during plant growth and development.
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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 | 0.001 | 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".