Disclosing the actual efficiency of G-quadruplex-DNA–disrupting small molecules
Bibliographic record
Abstract
Abstract The quest for small molecules that avidly bind to G-quadruplex-DNA (G4-DNA, or G4), so called G4-ligands, has invigorated the G4 research field from its very inception. Massive efforts have been invested to i - screen or design G4-ligands, ii - evaluate their G4-interacting properties in vitro through a series of now widely accepted and routinely implemented assays, and iii - use them as unique chemical biology tools to interrogate cellular networks that might involve G4s. In sharp contrast, only uncoordinated efforts at developing small molecules aimed at destabilizing G4s have been invested to date, even though it is now recognized that such molecular tools would have tremendous application to neurobiology as many genetic and age-related diseases are caused by an over-representation of G4s, itself caused by a deficiency of G4-resolving enzymes, the G4-helicases. Herein, we report on our double effort to i - develop a reliable in vitro assay to identify molecules able to destabilize G4s, the G4-unfold assay, and ii - fully characterize the first prototype of G4-disrupting small molecule, a phenylpyrrolcytosine (PhpC)-based G-clamp analog.
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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) | 0.000 | 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) | 0.002 | 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".