Structural characterization of S100A15 reveals a novel zinc coordination site among S100 proteins and altered surface chemistry with functional implications for receptor binding
Bibliographic record
Abstract
BACKGROUND: S100 proteins are a family of small, EF-hand containing calcium-binding signaling proteins that are implicated in many cancers. While the majority of human S100 proteins share 25-65% sequence similarity, S100A7 and its recently identified paralog, S100A15, display 93% sequence identity. Intriguingly, however, S100A7 and S100A15 serve distinct roles in inflammatory skin disease; S100A7 signals through the receptor for advanced glycation products (RAGE) in a zinc-dependent manner, while S100A15 signals through a yet unidentified G-protein coupled receptor in a zinc-independent manner. Of the seven divergent residues that differentiate S100A7 and S100A15, four cluster in a zinc-binding region and the remaining three localize to a predicted receptor-binding surface. RESULTS: To investigate the structural and functional consequences of these divergent clusters, we report the X-ray crystal structures of S100A15 and S100A7D24G, a hybrid variant where the zinc ligand Asp24 of S100A7 has been substituted with the glycine of S100A15, to 1.7 Å and 1.6 Å resolution, respectively. Remarkably, despite replacement of the Asp ligand, zinc binding is retained at the S100A15 dimer interface with distorted tetrahedral geometry and a chloride ion serving as an exogenous fourth ligand. Zinc binding was confirmed using anomalous difference maps and solution binding studies that revealed similar affinities of zinc for S100A15 and S100A7. Additionally, the predicted receptor-binding surface on S100A7 is substantially more basic in S100A15 without incurring structural rearrangement. CONCLUSIONS: Here we demonstrate that S100A15 retains the ability to coordinate zinc through incorporation of an exogenous ligand resulting in a unique zinc-binding site among S100 proteins. The altered surface chemistry between S100A7 and S100A15 that localizes to the predicted receptor binding site is likely responsible for the differential recognition of distinct protein targets. Collectively, these data provide novel insight into the structural and functional consequences of the divergent surfaces between S100A7 and S100A15 that may be exploited for targeted therapies.
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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".