Cofactor Directed Catalysis.
Bibliographic record
Abstract
Abstract Blood coagulation involves specific serine proteases that are activated by limited proteolysis. The process results in the conversion of prothrombin to thrombin which in turn cleaves fibrinogen to produce the insoluble fibrin mesh. Prothrombin is activated physiologically by the prothrombinase complex, which is composed of the non-enzymatic cofactor, factor Va, the enzyme, factor Xa, and the substrate prothrombin associated on a cell membrane-surface in the presence of Ca2+. Membrane-bound factor Xa alone can activate prothrombin by two sequential cleavages at R271 and R320, however the incorporation of Factor Va into prothrombinase results in the reversal of the order of cleavages, different intermediates being generated, and a 300,000-fold increase in the overall rate of catalysis. Initial cleavage at R271 will produce fragment 1•2 and prethrombin-2 while initial cleavage at R320 results in the formation of meizothrombin which has optimum esterase activity and diminished clotting activity. While the existence of these pathways and the kinetics of the rates of the cleavages have long been established, the consequences of the interaction of the cofactor with the components of prothrombinase and the molecular mechanism by which factor Va reverses the order of cleavages and increases the rate of the overall catalysis is unknown. We used recombinant factor Va molecules mutated at specific sites representing the binding domains of factor Va heavy chain for factor Xa (factor Va with the mutations E323 → F, Y324 → F, E330 → M, and V331 → I, factor VaFF/MI) and prothrombin (factor Va with the mutations D695 → K, Y696 → F, D697 → K, and Y698 → F, factor Va2K2F) in combination with plasma-derived prothrombin and mutant prothrombin molecules rMZ-II (prothrombin with the substitution R155 → A, R284 → A, and R271 → A) and rP2-II (prothrombin with the substitutions R155 → A, R284 → A, and R320 → A) to determine the molecular contribution of factor Va to each of the prothrombin-activating cleavage sites separately. The rate of cleavage of plasma-derived prothrombin at R320/R271 by prothrombinase assembled with factor VaFF/MI was 17-fold slower compared to prothrombinase assembled with the wild type cofactor. The incorporation of factor Va2K2F into prothrombinase resulted in an enzymatic complex that was both unable to activate plasma-derived prothrombin following initial cleavages at R320, and impaired in its ability to accelerate prothrombin activation through initial cleavage R271. Similarly, while the rates of cleavage of rMZ-II and rP2-II by prothrombinase assembled with factor VaFF/MI were 18- and 9-fold respectively slower compared to prothrombinase assembled with wild type factor Va, cleavage of both molecules by prothrombinase assembled with factor Va2K2F was considerly impaired. These data demonstrate that while the interaction of factor Va heavy chain with factor Xa is necessary to achieve optimal rates for thrombin formation, the interaction of factor Va with prothrombin is required because it promotes both initial cleavage at R320 and accelerates the rate of the cleavage at R271. The data presented herein dissects the cofactor’s contribution to the rate of each of the two prothrombin-activating cleavage sites, demonstrates that the interaction of factor Va heavy chain with prothrombin is responsible for the reversal of cleavage order, and strongly suggest that factor Va directs catalysis by factor Xa within prothrombinase at two spatially distinct sites.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.020 |
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".