Subtilase-like pro-protein convertases: from molecular specificity to therapeutic applications
Bibliographic record
Abstract
Limited proteolysis of most large protein precursors is carried out in vivo by the subtilisin-like pro-protein convertases. Many important biological processes such as peptide hormone synthesis, viral protein processing and receptor maturation involve proteolytic processing by these enzymes, making them potential targets for the development of novel therapeutic agents. However, the efficient development of such molecules requires a better understanding of the molecular mechanisms of proteolytic protein processing. Herein, we review the most recent findings on the molecular aspects of subtilisin-like convertase activity, such as the structural analysis of the proteases, the mechanisms of enzyme/substrate specificity, their interaction with other proteins such as 7B2, and the comparative tissue and cellular distribution of the enzymes and their substrates. These data are then used as a background for the review of the known biological functions of subtilisin-like pro-protein convertases, the reported clinical cases involving proteolytic processing defects and, finally, the ongoing development of new therapeutic inhibitor molecules based on this knowledge.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".