The structure of the SBP-Tag–streptavidin complex reveals a novel helical scaffold bridging binding pockets on separate subunits
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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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 | 0.001 | 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".