Annexin A2-S100A10 Heterotetramer, a Novel Substrate of Thioredoxin
Bibliographic record
Abstract
The binding of plasminogen activators and plasminogen to the cell surface results in the rapid generation of the serine protease plasmin. Plasmin is further degraded by an autoproteolytic reaction, resulting in the release of an angiostatin, A61 (Lys78-Lys468). Previously, we demonstrated that the annexin A2-S100A10 heterotetramer (AIIt) stimulates the release of A61 from plasmin by promoting the autoproteolytic cleavage of the Lys468-Gly469 bond and reduction of the plasmin Cys462-Cys541 disulfide (Kwon, M., Caplan, J. F., Filipenko, N. R., Choi, K. S., Fitzpatrick, S. L., Zhang, L., and Waisman, D. M. (2002) J. Biol. Chem. 277, 10903-10911). Mechanistically, it was unclear if AIIt promoted a conformational change in plasmin, resulting in contortion of the plasmin disulfide, or directly reduced the plasmin disulfide. In the present study, we show that AIIt thiols are oxidized during the reduction of plasmin disulfides, establishing that AIIt directly participates in the reduction reaction. Incubation of HT1080 cells with plasminogen resulted in the rapid loss of thiol-specific labeling of AIIt by 3-(N-maleimidopropionyl)biocytin. The plasminogen-dependent oxidation of AIIt could be attenuated by thioredoxin. Thioredoxin reductase catalyzed the transfer of electrons from NADPH to the oxidized thioredoxin, thus completing the flow of electrons from NADPH to AIIt. Therefore, we identify AIIt as a substrate of the thioredoxin system and propose a new model for the role of AIIt in the redox-dependent processing of plasminogen and generation of an angiostatin at the cell surface.
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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".