Apolactoferrin inhibits the catalytic domain of matrix metalloproteinase-2 by zinc chelation
Bibliographic record
Abstract
Lactoferrin (LTF) is a multifunctional iron-binding protein that is also capable of binding other divalent metal cations, especially Zn2+. Recent investigations indicate that lactoferrin levels are elevated in many disease conditions in which matrix metalloproteinases (MMPs), particularly MMP-2, are also elevated, suggesting that the 2 proteins may interact. This possibility was examined by determining the effect of LTF in its holo (metal-bound) and apo (metal-free) forms on the proteolytic activity of MMP-2 and other similar zinc metalloproteases. Pre-incubation with apolactoferrin, but not hololactoferrin, greatly reduced the hydrolysis of a peptide substrate by MMP-2, but not by MMP-1, -8, -9, or -13. This inhibition was specific for the 42 kDa catalytic domain fragment of MMP-2 lacking the hemopexin domain, since the 66 kDa form was poorly inhibited by apolactoferrin. The inhibition of the MMP-2 catalytic domain was strongly temperature sensitive, indicating that the conformation of one or both proteins is crucial to this interaction. To ascertain the mechanism of inhibition, increasing concentrations of ZnCl2 and FeCl2 were added to the reaction. While addition of Fe2+ did not reverse inhibition, the addition of Zn2+ resulted in a recovery of MMP-2 activity, and furthermore, zinc-saturated LTF did not inhibit MMP-2. Together, these data strongly suggest that apolactoferrin is capable of removing the catalytic zinc from the active site of MMP-2, although an exosite-based interaction between the 2 proteins cannot be fully ruled out. This inhibitory activity suggests a novel function for LTF and may represent a novel regulatory mechanism that regulates proteolysis by MMP-2 in vivo.
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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 | 0.000 |
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".