Kinetics of Activated Thrombin-activatable Fibrinolysis Inhibitor (TAFIa)-catalyzed Cleavage of C-terminal Lysine Residues of Fibrin Degradation Products and Removal of Plasminogen-binding Sites
Bibliographic record
Abstract
Partial digestion of fibrin by plasmin exposes C-terminal lysine residues, which comprise new binding sites for both plasminogen and tissue-type plasminogen activator (tPA). This binding increases the catalytic efficiency of plasminogen activation by 3000-fold compared with tPA alone. The activated thrombin-activatable fibrinolysis inhibitor (TAFIa) attenuates fibrinolysis by removing these residues, which causes a 97% reduction in tPA catalytic efficiency. The aim of this study was to determine the kinetics of TAFIa-catalyzed lysine cleavage from fibrin degradation products and the kinetics of loss of plasminogen-binding sites. We show that the k(cat) and K(m) of Glu(1)-plasminogen (Glu-Pg)-binding site removal are 2.34 s(-1) and 142.6 nm, respectively, implying a catalytic efficiency of 16.21 μm(-1) s(-1). The corresponding values of Lys(77)/Lys(78)-plasminogen (Lys-Pg)-binding site removal are 0.89 s(-1) and 96 nm implying a catalytic efficiency of 9.23 μm(-1) s(-1). These catalytic efficiencies of plasminogen-binding site removal by TAFIa are the highest of any TAFIa-catalyzed reaction with a biological substrate reported to date and suggest that plasmin-modified fibrin is a primary physiological substrate for TAFIa. We also show that the catalytic efficiency of cleavage of all C-terminal lysine residues, whether they are involved in plasminogen binding or not, is 1.10 μm(-1) s(-1). Interestingly, this value increases to 3.85 μm(-1) s(-1) in the presence of Glu-Pg. These changes are due to a decrease in K(m). This suggests that an interaction between TAFIa and plasminogen comprises a component of the reaction mechanism, the plausibility of which was established by showing that TAFIa binds both Glu-Pg and Lys-Pg.
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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 | 0.001 | 0.001 |
| 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".