TIMP Independence of Matrix Metalloproteinase (MMP)-2 Activation by Membrane Type 2 (MT2)-MMP Is Determined by Contributions of Both the MT2-MMP Catalytic and Hemopexin C Domains
Bibliographic record
Abstract
The important and distinct contribution that membrane type 2 (MT2)-matrix metalloproteinase (MMP) makes to physiological and pathological processes is now being recognized. This contribution may be mediated in part through MMP-2 activation by MT2-MMP. Using Timp2-/- cells, we previously demonstrated that MT2-MMP activates MMP-2 to the fully active form in a pathway that is TIMP-2-independent but MMP-2 hemopexin carboxyl (C) domain-dependent. In this study cells expressing MT2-MMP as well as chimera proteins in which the C-terminal half of MT2-MMP and MT1-MMP were exchanged showed that the MT2-MMP catalytic domain has a higher propensity than that of MT1-MMP to initiate cleavage of the MMP-2 prodomain in the absence of TIMP-2. Although we demonstrate that MT2-MMP is a weak collagenase, this first activation cleavage was enhanced by growing the cells in type I collagen gels. The second activation cleavage to generate fully active MMP-2 was specifically enhanced by a soluble factor expressed by Timp2-/- cells and was MT2-MMP hemopexin C domain-dependent; however, the RGD sequence within this domain was not involved. Interestingly, in the presence of TIMP-2, a MT2-MMP.MMP-2 trimolecular complex formed, but activation was not enhanced. Similarly, TIMP-3 did not promote MT2-MMP-mediated MMP-2 activation but inhibited activation at higher concentrations. This study demonstrates the influence that both the catalytic and hemopexin C domains of MT2-MMP exert in determining TIMP independence in MMP-2 activation. In tissues or pathologies characterized by low TIMP-2 expression, this pathway may represent an alternative means of rapidly generating low levels of active MMP-2.
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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) | 0.002 | 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".