The Annexin A2/S100A10 Complex: The Mutualistic Symbiosis of Two Distinct Proteins
Bibliographic record
Abstract
Mutualistic symbiosis refers to the symbiotic relationship between individuals of different species in which both individuals benefit from the association. S100A10, a member of the S100 family of Ca2+-binding proteins, exists as a tight dimer and binds two annexin A2 molecules. This association forms the annexin A2/S100A10 complex known as AIIt, and modifies the distinct functions of both proteins. Annexin A2 is a Ca2+-binding protein that binds F-actin, phospholipid, RNA, and specific polysaccharides such as heparin. S100A10 does not bind Ca2+, but binds tPA, plasminogen, certain plasma membrane ion channels, neurotransmitter receptors, and the structural scaffold protein, AHNAK. S100A10 relies on annexin A2 for its intracellular survival: in the absence of annexin A2, it is rapidly destroyed by ubiquitin-dependent and independent proteasomal degradation. Annexin A2 requires S100A10 to increase its affinity for Ca2+, facilitating its participation in Ca2+-dependent processes such as membrane binding. S100A10 binds tissue plasminogen activator and plasminogen, and promotes plasminogen activation to plasmin, which is a process stimulated by annexin A2. In contrast, annexin A2 acts as a plasmin reductase and facilitates the autoproteolytic destruction of plasmin. This review examines the relationship between annexin A2 and S100A10, and how their mutualistic symbiosis affects the function of both proteins.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".