Acetylation of 1,2,5,8-tetrahydroxy-9,10-anthraquinone Improves Binding to DNA and Shows Enhanced Superoxide Formation that Explains Better Cytotoxicity on JURKAT T Lymphocyte Cells
Bibliographic record
Abstract
Background: Hydroxy-9,10-anthraquinones form the core unit of anthracycline anticancer drugs and are close structural analogues to these drugs. Although they show close resemblance to anthracyclines in physicochemical characteristics and electrochemical behavior their biophysical interactions are somewhat weaker than anthracyclines which is a disadvantage. One reason is the formation of anionic species by hydroxy-9,10-anthraquinones. Hence if formation of anionic species is prevented there could be a possibility hydroxy-9,10-anthraquinones would bind DNA better. Procedure: For this 1, 2, 5, 8-tetrahydroxy-9,10-anthraquinone (THAQ) was acetylated to obtain a tetra-acetylated derivative (THAQ-ace) whose interaction with calf thymus DNA was studied using UV-Vis spectroscopy at different pH. Results: Binding constant values for THAQ-ace (~105) were higher than THAQ at different pH. Increase in binding constant was attributed to anionic species not formed for THAQ-ace at physiological pH. Hence, unlike THAQ, binding constant values for THAQ-ace interacting with calf thymus DNA did not show variation with pH. In fact, it remained more or less constant. Increase in size of the acetylated form (THAQ-ace) compared to THAQ had a negative influence on binding. THAQ-ace showed enhanced superoxide formation. Both DNA binding and superoxide formation were responsible for a significant improvement in anticancer activity for THAQ-ace compared to THAQ on Jurkat T lymphocyte cells. Conclusion: Binding constant values for THAQ-ace binding to DNA were close to that reported for some standard anthracyclines. Hence, suitable modification of the less costly hydroxy-9,10-anthraquinones could provide alternatives to anthracyclines in cancer chemotherapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".