ADAM17 is regulated by a rapid and reversible mechanism that controls access to its catalytic site
Bibliographic record
Abstract
Protein ectodomain shedding is crucial for cell-cell interactions because it controls the bioavailability of soluble tumor necrosis factor-α (TNFα) and ligands of the epidermal growth factor (EGF) receptor, and the release of many other membrane proteins. Various stimuli can rapidly trigger ectodomain shedding, yet much remains to be learned about the identity of the enzymes that respond to these stimuli and the mechanisms underlying their activation. Here, we demonstrate that the membrane-anchored metalloproteinase ADAM17, but not ADAM10, is the sheddase that rapidly responds to the physiological signaling pathways stimulated by thrombin, EGF, lysophosphatidic acid and TNFα. Stimulation of ADAM17 is swift and quickly reversible, and does not depend on removal of its inhibitory pro-domain by pro-protein convertases, or on dissociation of an endogenous inhibitor, TIMP3. Moreover, activation of ADAM17 by physiological stimuli requires its transmembrane domain, but not its cytoplasmic domain, arguing against inside-out signaling via cytoplasmic phosphorylation as the underlying mechanism. Finally, experiments with the tight binding hydroxamate inhibitor DPC333, used here to probe the accessibility of the active site of ADAM17, demonstrate that this inhibitor can quickly bind to ADAM17 in stimulated, but not quiescent cells. These findings support the concept that activation of ADAM17 involves a rapid and reversible exposure of its catalytic site.
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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 | 0.001 |
| 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".