Kinetic Analysis of a Unique Direct Prothrombinase, <i>fgl2</i> , and Identification of a Serine Residue Critical for the Prothrombinase Activity
Bibliographic record
Abstract
fgl2 prothrombinase, by its ability to generate thrombin, has been shown to be pivotal to the pathogenesis of viral-induced hepatitis, cytokine-induced fetal loss syndrome, and xeno- and allograft rejection. In this study, the molecular basis of fgl2 prothrombinase activity was examined in detail. Purified fgl2 protein generated in a baculovirus expression system had no measurable prothrombinase activity, whereas the activity was restored when the purified protein was reconstituted into phosphatidyl-L-serine-containing vesicles. Reconstituted fgl2 catalyzed the cleavage of human prothrombin to thrombin with kinetics consistent with a first order reaction, with an apparent V(max) value of 6 mol/min/mol fgl2 and an apparent K(m) value for prothrombin of 8.3 microM. The catalytic activity was totally dependent on calcium, and factor Va (500 nM) enhanced the catalytic efficiency of fgl2 by increasing the apparent V(max) value to 3670 mol/min/mol fgl2 and decreasing the apparent K(m) value for prothrombin to 7.2 microM. By a combination of site-directed mutagenesis and production of truncated proteins, it was clearly shown that residue Ser(89) was critical for the prothrombinase activity of fgl2. Furthermore, fgl2 prothrombinase activity was not inhibited by antithrombin III, soybean trypsin inhibitor, 4-aminobenzamidine, aprotinin, or phenylmethylsulfonyl fluoride, whereas diisopropylfluorophosphate completely abrogated the activity. In this work we provide direct evidence that fgl2 cleaves prothrombin to thrombin consistent with serine protease activity and requires calcium, phospholipids, and factor Va for its full activity.
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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".