A simple and sensitive detection of small molecule–protein interactions based on terminal protection-mediated exponential strand displacement amplification
Bibliographic record
Abstract
We herein describe a simple and sensitive strategy to detect a small molecule-protein interaction based on terminal protection-mediated exponential strand displacement amplification (eSDA). In principle, the small molecule linked to a DNA probe protects the DNA probe against the exonuclease I-catalyzed degradation after its binding to the corresponding target protein. The protected DNA probe then serves as a template to promote eSDA. Consequently, a large number of duplexes are produced, which leads to a high fluorescence from a double-stranded DNA specific fluorescent dye, SYBR Green I. As a model system to prove this sensing strategy, the interaction between biotin and streptavidin (SA), which is known to be the strongest among the non-covalent biological interactions, was selected and its analytical performance was thoroughly investigated. As a result, SA was sensitively detected with the limit of detection of 16 pM. In addition, the practical applicability of this method was successfully demonstrated by reliably determining the SA in human serum.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".