Proteomic Analyses Reveal an Acidic Prime Side Specificity for the Astacin Metalloprotease Family Reflected by Physiological Substrates
Bibliographic record
Abstract
Astacins are secreted and membrane-bound metalloproteases with clear associations to many important pathological and physiological processes. Yet with only a few substrates described their biological roles are enigmatic. Moreover, the lack of knowledge of astacin cleavage site specificities hampers assay and drug development. Using PICS (proteomic identification of protease cleavage site specificity) and TAILS (terminal amine isotopic labeling of substrates) degradomics approaches >3000 cleavage sites were proteomically identified for five different astacins. Such broad coverage enables family-wide determination of specificities N- and C-terminal to the scissile peptide bond. Remarkably, meprin α, meprin β, and LAST_MAM proteases exhibit a strong preference for aspartate in the peptide (P)1' position because of a conserved positively charged residue in the active cleft subsite (S)1'. This unparalleled specificity has not been found for other families of extracellular proteases. Interestingly, cleavage specificity is also strongly influenced by proline in P2' or P3' leading to a rare example of subsite cooperativity. This specificity characterizes the astacins as unique contributors to extracellular proteolysis that is corroborated by known cleavage sites in procollagen I+III, VEGF (vascular endothelial growth factor)-A, IL (interleukin)-1β, and pro-kallikrein 7. Indeed, cleavage sites in VEGF-A and pro-kallikrein 7 identified by terminal amine isotopic labeling of substrates matched those reported by Edman degradation. Moreover, the novel substrate FGF-19 was validated biochemically and shown to exhibit altered biological activity after meprin processing.
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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 | 0.000 |
| 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".