Factor Va Cofactor Activity Is Dependent on the Interaction of Prothrombin with the Membrane Surface.
Bibliographic record
Abstract
Abstract Activation of human prothrombin (Pro) occurs because of two sequential cleavages in prothrombin by membrane-bound factor Xa (fXa) (Arg271 followed by Arg320, prethrombin 2 pathway). However, the catalytic efficiency of membrane-bound fXa is poor in the absence of factor Va (fVa), and the overall reaction is incompatible with efficient thrombin formation required for the timely arrest of bleeding. Binding of fVa to fXa on a membrane surface in the presence of divalent metal ions results in the formation of prothrombinase. This complex catalyzes the activation of Pro following the opposite pathway (cleavage at Arg320 followed by Arg271, meizothrombin pathway). This pathway results in a dramatic increase in the catalytic efficiency of fXa. It is well established that initial cleavage of prothrombin at Arg320 is strictly dependent on the incorporation of fVa into prothrombinase and that the increase in the overall efficiency of the enzymatic reaction is solely credited to the interaction of the cofactor molecule with discrete amino acid residues from both membrane-bound enzyme and membrane-bound substrate. Thus, the activity of fXa within prothrombinase is controlled by the presence of the soluble, non-enzymatic cofactor, fVa. We have shown that a pentapeptide with the sequence DYDYQ specifically inhibits this pathway. It has been also established that Hir54–65(SO3−) is a specific inhibitor of prothrombinase. To understand the role of fVa within prothrombinase at the molecular level, we have studied thrombin formation by prothrombinase in the presence of various Pro-derived fragments alone or in combination. Activation of prethrombin 1 is slow with cleavages at Arg320 and Arg271 occurring with similar rates. Addition of purified fragment 1 to prethrombin 1 accelerates both the rate of cleavage at Arg320 and thrombin formation. Both reactions were inhibited by Hir54–65(SO3−) while DYDYQ had no significant inhibitory effect on prethrombin 1 cleavage in the absence or presence of fragment Similarly, activation of prethrombin 2 by prothrombinase, which is notably slow and inhibited by Hir54–65(SO3−), is not affected by DYDYQ. Addition of purified fragment 1·2 to prethrombin 2 accelerates the rate of cleavage at Arg320 by prothrombinase resulting in a rate of thrombin formation comparable to the rate of Pro activation by prothrombinase. This addition results in a significant inhibition of thrombin formation by DYDYQ and is concurrent with the elimination of the inhibitory effect of Hir54–65(SO3−) on the same reaction. Finally, a membrane-bound ternary complex composed of prethrombin 2/fragment 1·2/Hir54–65(SO3−) is inhibited by DYDYQ. These data demonstrate that DYDYQ and Hir54–65(SO3−) inhibit prothrombinase activity through different mechanisms because the peptides most likely interact with distinct portions of prethrombin Altogether, the data demonstrate that membrane-bound fragment 1 is required to promote optimum fVa cofactor activity which in turn is translated by efficient initial cleavage of Pro by prothrombinase at Arg320. Therefore, our findings put in the context of the literature suggest that fVa incorporation into prothrombinase equalizes the rate of both Pro activating cleavages, and it is the interaction of membrane-bound fragment 1 with fVa and/or fXa within prothrombinase that promotes a further accelerating effect of the rate of cleavage at Arg320, resulting in meizothrombin generation.
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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) | 0.002 | 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".