Conformational Dynamics of DNA G‐Quadruplex in Solution Studied by Kinetic Capillary Electrophoresis Coupled On‐line with Mass Spectrometry
Bibliographic record
Abstract
G-quadruplex-forming DNA/RNA sequences play an important role in the regulation of biological functions and development of new anticancer and anti-aging drugs. In this work, we couple on-line kinetic capillary electrophoresis with mass spectrometry (KCE-MS) to study conformational dynamics of DNA G-quadruplexes in solution. We show that peaks shift and its widening in KCE can be used for measuring rate and equilibrium constants for DNA-metal affinity interactions and G-quadruplex formation; and ion mobility mass spectrometry (IM-MS) provides information about relative sizes, absolute molecular masses and stoichiometry of DNA complexes. KCE-MS separates a thrombin-binding aptamer d[GGTTGGTGTGGTTGG] from mutated sequences based on affinity to potassium, and reveals the apparent equilibrium folding constant (K F≈150 μm), folding rate constant (k on≈1.70×10(3) s(-1) m(-1)), unfolding rate constant (k off≈0.25 s(-1)), half-life time of the G-quadruplex (t 1/2≈2.8 s), and relaxation time (τ≈3.9 ms at physiological 150 mm [K(+)]). In addition, KCE-MS screens for a GQ-stabilizing/-destabilizing effect of DNA binding dyes and an anticancer drug, cisplatin.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".