Identification of heparin interaction sites on thrombin-activatable fibrinolysis inhibitor that modulate plasmin-mediated activation, thermal stability, and antifibrinolytic potential
Bibliographic record
Abstract
Background: Thrombin-activatable fibrinolysis inhibitor (TAFI) is a plasma zymogen that provides a molecular link between coagulation and fibrinolysis. Studies have shown that the presence of glycosaminoglycans accelerates TAFI activation by plasmin and stabilizes activated TAFI (TAFIa). Objectives: We aimed to define the elements of TAFI structure that allow these effects. Methods: Based on crystallographic studies and homology to heparin-binding proteins, we performed mutagenesis of surface-exposed charged residues on TAFI that putatively constitute heparin-binding sites. We determined heparin binding, kinetics of activation by plasmin in the presence or absence of heparin, thermal stability, and antifibrinolytic potential of each variant. Results: Mutagenesis of Lys211 and Lys212 did not impair heparin binding but affected the ability of TAFI to be activated by plasmin. Mutagenesis of Lys306 and His308 did not impair heparin binding, but mutation of His308 had a severe negative effect on TAFI/TAFIa function. Mutation of Arg320 and Lys324 in combination markedly decreased heparin binding but had no effect on heparin-mediated acceleration of TAFI activation by plasmin while somewhat decreasing TAFIa stabilization by heparin. Mutagenesis of Lys327 and Arg330 decreased (but did not eliminate) heparin binding while decreasing the ability of heparin to accelerate plasmin-mediated TAFI activation, stabilize TAFIa, and increase the antifibrinolytic ability of TAFIa. A quadruple mutant of Arg320, Lys324, Lys327, and Arg330 completely lost heparin-binding ability and stabilization of the enzyme by heparin. Conclusion: Basic residues in the dynamic flap of TAFIa define a functionally relevant heparin-binding site, but additional heparin-binding sites may be present on TAFI.
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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".