The structure of the SBP-Tag–streptavidin complex reveals a novel helical scaffold bridging binding pockets on separate subunits
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Bibliographic record
Abstract
The 38-residue SBP-Tag binds to streptavidin more tightly (K(d) -/= 2.5-4.9 nM) than most if not all other known peptide sequences. Crystallographic analysis at 1.75 Å resolution shows that the SBP-Tag binds to streptavidin in an unprecedented manner by simultaneously interacting with biotin-binding pockets from two separate subunits. An N-terminal HVV peptide sequence (residues 12-14) and a C-terminal HPQ sequence (residues 31-33) form the bulk of the direct interactions between the SBP-Tag and the two biotin-binding pockets. Surprisingly, most of the peptide spanning these two sites (residues 17-28) adopts a regular α-helical structure that projects three leucine side chains into a groove formed at the interface between two streptavidin protomers. The crystal structure shows that residues 1-10 and 35-38 of the original SBP-Tag identified through in vitro selection and deletion analysis do not appear to contact streptavidin and thus may not be important for binding. A 25-residue peptide comprising residues 11-34 (SBP-Tag2) was synthesized and shown using surface plasmon resonance to bind streptavidin with very similar affinity and kinetics when compared with the SBP-Tag. The SBP-Tag2 was also added to the C-terminus of β-lactamase and was shown to be just as effective as the full-length SBP-Tag in affinity purification. These results validate the molecular structure of the SBP-Tag-streptavidin complex and establish a minimal bivalent streptavidin-binding tag from which further rational design and optimization can proceed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it