Structure-Guided Design of an Engineered Streptavidin with Reusability to Purify Streptavidin-Binding Peptide Tagged Proteins or Biotinylated Proteins
Bibliographic record
Abstract
Development of a high-affinity streptavidin-binding peptide (SBP) tag allows the tagged recombinant proteins to be affinity purified using the streptavidin matrix without the need of biotinylation. The major limitation of this powerful technology is the requirement to use biotin to elute the SBP-tagged proteins from the streptavidin matrix. Tight biotin binding by streptavidin essentially allows the matrix to be used only once. To address this problem, differences in interactions of biotin and SBP with streptavidin were explored. Loop3-4 which serves as a mobile lid for the biotin binding pocket in streptavidin is in the closed state with biotin binding. In contrast, this loop is in the open state with SBP binding. Replacement of glycine-48 with a bulkier residue (threonine) in this loop selectively reduces the biotin binding affinity (Kd) from 4 × 10(-14) M to 4.45 × 10(-10) M without affecting the SBP binding affinity. Introduction of a second mutation (S27A) to the first mutein (G48T) results in the development of a novel engineered streptavidin SAVSBPM18 which could be recombinantly produced in the functional form from Bacillus subtilis via secretion. To form an intact binding pocket for tight binding of SBP, two diagonally oriented subunits in a tetrameric streptavidin are required. It is vital for SAVSBPM18 to be stably in the tetrameric state in solution. This was confirmed using an HPLC/Laser light scattering system. SAVSBPM18 retains high binding affinity to SBP but has reversible biotin binding capability. The SAVSBPM18 matrix can be applied to affinity purify SBP-tagged proteins or biotinylated molecules to homogeneity with high recovery in a reusable manner. A mild washing step is sufficient to regenerate the matrix which can be reused for multiple rounds. Other applications including development of automated protein purification systems, lab-on-a-chip micro-devices, reusable biosensors, bioreactors and microarrays, and strippable detection agents for various blots are possible.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".