Analysis of the Kinetics of Prothrombin Activation and Evidence That Two Equilibrating Forms of Prothrombinase Are Involved in the Process
Bibliographic record
Abstract
Prothrombinase cleaves prothrombin at Arg(271) and Arg(320) to produce thrombin. The kinetics of cleavage of five recombinant prothrombins were measured: wild-type prothrombin (WT-II), R155A/R284A/R271A prothrombin (rMZ-II), R155A/R284A/R320A prothrombin (rP2-II), S525C prothrombin labeled with fluorescein (WT-II-F*), and R155A/R284A/R271A/S525C prothrombin labeled with fluorescein (rMZ-II-F*). rMZ-II and rP2-II are cleaved only at Arg(320) and Arg(271), respectively, to yield the intermediates meizothrombin and prethrombin-2, respectively. WT-II-F* and rMZ-II-F* were labeled at Cys(525) with fluorescein; cleavage was monitored by enhanced fluorescence. Activation kinetics of WT-II, rMZ-II, and rP2-II indicated that the catalytic efficiency of cleavage at Arg(320) was increased by 30,000-fold by the cofactor factor Va, as was the conversion of prothrombin to thrombin. However, factor Va increased cleavage at Arg(271) only by 34-fold. Although WT-II competitively inhibited cleavage of WT-II-F*, rMZ-II or rP2-II did not inhibit completely even at saturating concentrations. However, rMZ-II and rP2-II together inhibited WT-II-F* cleavage competitively. Both WT-II and rMZ-II competitively inhibited rMZ-II-F* cleavage, whereas rP2-II did not. A model of prothrombin activation that includes two equilibrating forms of prothrombinase, each recognizing one of the cleavage sites, is quantitatively consistent with all of the experimental observations. Therefore, we conclude that the kinetics of prothrombin activation can be described by a "ping-pong"-like mechanism.
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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 | 0.001 |
| 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".