Engineering monomeric streptavidin and its ligands with infinite affinity in binding but reversibility in interaction
Bibliographic record
Abstract
Natural tetrameric streptavidin captures and immobilizes biotinylated molecules with ultra-tight binding (K(d) approximately 10(-13) to 10(-14) M). In contrast, engineered monomeric streptavidin offers reversible binding (K(d) approximately 10(-7) M). To develop an ideal engineered streptavidin which possesses both the immobilization capability of the natural streptavidin and the reversible interaction reactivity of the monomeric streptavidin, a pair of engineered biomaterials was designed through molecular modeling. This system consists of two recombinant components: an engineered monomeric streptavidin M6, which has a cysteine residue (C118) near the biotin binding site, and a cysteine containing biotinylation tag. Interactions between M6 and the biotinylated peptide tag go through a two-stage process (capture and immobilization) to generate a covalently linked complex. Biotinylation is essential in the capture stage. Once the biotin moiety in the biotinylated tag is captured by M6, the biotinylated tag can fold back and rotate on the surface of the complex with the biotinylated lysine in the peptide tag as the axis until the formationof a disulfide bond. Consequently, cysteine residue in different positions flanking the biotin residue in the biotinylation tag can successfully form a disulfide bond with M6. Intermolecular disulfide bond formation between M6 and the tag containing protein offers the immobilization capability to M6. In the presence of reducing agent and biotin, bound ligands can be dissociated. This system has the potential to extend the biotin-streptavidin technology to develop reusable biosensor/protein chips and bioreactors.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".