Both Ca2+ and Zn2+ are essential for S100A12 protein oligomerization and function
Bibliographic record
Abstract
BACKGROUND: Human S100A12 is a member of the S100 family of EF-hand calcium-modulated proteins that are associated with many diseases including cancer, chronic inflammation and neurological disorders. S100A12 is an important factor in host/parasite defenses and in the inflammatory response. Like several other S100 proteins, it binds zinc and copper in addition to calcium. Mechanisms of zinc regulation have been proposed for a number of S100 proteins e.g. S100B, S100A2, S100A7, S100A8/9. The interaction of S100 proteins with their targets is strongly dependent on cellular microenvironment. RESULTS: The aim of the study was to explore the factors that influence S100A12 oligomerization and target interaction. A comprehensive series of biochemical and biophysical experiments indicated that changes in the concentration of calcium and zinc led to changes in the oligomeric state of S100A12. Surface plasmon resonance confirmed that the presence of both calcium and zinc is essential for the interaction of S100A12 with one of its extracellular targets, RAGE--the Receptor for Advanced Glycation End products. By using a single-molecule approach we have shown that the presence of zinc in tissue culture medium favors both the oligomerization of exogenous S100A12 protein and its interaction with targets on the cell surface. CONCLUSION: We have shown that oligomerization and target recognition by S100A12 is regulated by both zinc and calcium. Our present work highlighted the potential role of calcium-binding S100 proteins in zinc metabolism and, in particular, the role of S100A12 in the cross talk between zinc and calcium in cell signaling.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".