Dissociation Constant (<i>K</i><sub>d</sub>) Measurement for Small‐Molecule Binding Aptamers: Homogeneous Assay Methods and Critical Evaluations
Bibliographic record
Abstract
Abstract Since 1990, numerous aptamers have been isolated and discovered for use in various analytical, biomedical, and environmental applications. This trend continues to date. A critical step in the characterization of aptamer binding is to measure its binding affinity toward both target and non‐target molecules. Dissociation constant (Kd) is the most commonly used value in characterizing aptamer binding. In this article, homogenous assays are reviewed for aptamers that can bind small‐molecule targets. The reviewed methods include label‐free methods, such as isothermal titration calorimetry, intrinsic fluorescence of target molecules, DNA staining dyes, and nuclease digestion assays, and labeled methods, such as the strand displacement reaction. Some methods are not recommended, such as those based on the aggregation of gold nanoparticles and the desorption of fluorophore‐labeled DNA from nanomaterials. The difference between the measured apparent Kd and the true Kd of aptamer binding is stressed. In addition, avoiding the titration regime and paying attention to the time required to reach equilibrium are discussed. Finally, it is important to include mutated non‐binding sequences as controls.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".