Long Range Communication between Exosites 1 and 2 Modulates Thrombin Function
Bibliographic record
Abstract
Although exosites 1 and 2 regulate thrombin activity by binding substrates and cofactors and by allosterically modulating the active site, it is unclear whether there is direct allosteric linkage between the two exosites. To begin to address this, we first titrated a thrombin variant fluorescently labeled at exosite 1 with exosite 2 ligands, HD22 (a DNA aptamer), gamma'-peptide (an analog of the COOH terminus of the gamma'-chain of fibrinogen) or heparin. Concentration-dependent and saturable changes in fluorescence were elicited, supporting inter-exosite linkage. To explore the functional consequences of this phenomenon, we evaluated the capacity of exosite 2 ligands to inhibit thrombin binding to gamma(A)/gamma(A)-fibrin, an interaction mediated solely by exosite 1. When gamma(A)/gamma(A)-fibrinogen was clotted with thrombin in the presence of HD22, gamma'-peptide, or prothrombin fragment 2 there was a dose-dependent and saturable decrease in thrombin binding to the resultant fibrin clots. Furthermore, HD22 reduced the affinity of thrombin for gamma(A)/gamma(A)-fibrin 6-fold and accelerated the dissociation of thrombin from preformed gamma(A)/gamma(A)-fibrin clots. Similar responses were obtained when surface plasmon resonance was used to monitor the interaction of thrombin with gamma(A)/gamma(A)-fibrinogen or fibrin. There is bidirectional communication between the exosites, because exosite 1 ligands, HD1 (a DNA aptamer) or hirudin-(54-65) (an analog of the COOH terminus of hirudin), inhibited the exosite 2-mediated interaction of thrombin with immobilized gamma'-peptide. These findings provide evidence for long range allosteric linkage between exosites 1 and 2 on thrombin, revealing further complexity to the mechanisms of thrombin regulation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".