The C-Terminus and Linker Region of S100B Exert Dual Control on Protein−Protein Interactions with TRTK-12
Bibliographic record
Abstract
S100B, an EF-hand calcium-binding protein composed of two S100beta monomers, undergoes a calcium-dependent conformational change that provides a surface for target interactions. In this study, the calcium-sensitive S100B-binding epitope TRTK-12 has been used to probe the contributions of the linker and C-terminal regions of S100B to protein-protein interactions. These contributions were quantified using C-terminal mutant S100B proteins lacking the C-terminal seven (S100B85stop) or nine (S100B83stop) residues or containing alanine substitutions at Phe87 (F87A), Phe88 (F88A), or both (F8788A). Both F8788A and F88A bound TRTK-12 less tightly (K(d) = 1.85 +/- 0.02 and 0.97 +/- 0.08 microM, respectively) than the wild-type protein (K(d) = 0.27 +/- 0.03 microM, DeltaG = -37.2 kJ/mol), indicating these residues are important for TRTK-12 interaction. The truncated S100B proteins bound TRTK-12 much more weakly (K(d) = 659.7 +/- 119.3 microM, DeltaG = -17.9 kJ/mol), indicating the linker region contributed about 50% to the binding of TRTK-12, while the C-terminus contributed the remaining 50% of the binding energy. Based on mutagenesis and NMR chemical shift studies, a comparison with known S100-target protein complexes showed the S100B-TRTK-12 complex has the strongest resemblance to the S100A10-annexin II interaction.
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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".