Synthesis and DNA-binding affinity studies of glycosylated intercalators designed as functional mimics of the anthracycline antibiotics
Bibliographic record
Abstract
Anthracycline antibiotics such as daunomycin (Dauno) and doxorubicin (Dox) are well-known clinically used cancer chemotherapeutics, which, among other mechanisms, bind to DNA, thereby triggering a cascade of biological responses leading to cell death. However, anthracyclines are cardiotoxic, and drug resistance develops rapidly, thus limiting their clinical use. We report here the synthesis and DNA-binding affinity of a novel class of functional anthracycline mimetics consisting of an aromatic moiety linked to a carbohydrate (1-12). In the targets, the aromatic core consists of a 2-phenylbenzo[b]furan-3-yl, 2-phenylbenzo[b]thiophen-3-yl, 1-tosyl-2-phenylindol-3-yl, or 2-phenylindol-3-yl group that is bound to one of three aminosugars (daunosamine, acosamine, or 4-amino-2,3,4,6-tetradeoxy-alpha-l-hexopyranoside) via a propargyl linker. The DNA binding affinity of these twelve compounds has been evaluated by using both direct and indirect fluorescence measurements. Compared to Dauno and Dox, the DNA binding affinity of these analogues is weaker. However, both aromatic and aminosugar motifs are critical to DNA binding, with more influence coming from the structural features of the aromatic portion.
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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) | 0.000 | 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 | 0.000 |
| 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".