Divalent later transition metal complexes of the traditional chinese medicine (TCM) liriodenine: coordination chemistry, cytotoxicity and DNA binding studies
Bibliographic record
Abstract
Liriodenine (L), a natural alkaloid, was isolated as an active component from the anticancer traditional Chinese medicine (TCM), Zanthoxylum nitidum. It reacted with Mn(II), Fe(II), Co(II) and Zn(II) to afford four metal complexes: [MnCl(2)(L)(2)] (1), [FeCl(2)(L)(2)] (2), [Co(L)(2)(H(2)O)(2).Co(L)(2)(CH(3)CH(2)OH)(2)](ClO(4))(4) (3), and [Zn(2)(L)(2)(mu(2)-Cl)(2)Cl(2)] (4), which were characterized by elemental analysis, IR, ESI-MS. Their crystal structures were determined by the single crystal X-ray diffraction method. The in vitro cytotoxicity of L and complexes 1-4 against 10 human tumour cell lines was assayed. Some of these metal-based compounds exhibited enhanced cytotoxicity vs. free L to selected tumour cell lines. The binding properties of L and its complexes 1-4 to ct-DNA were investigated by spectroscopic methods and viscosity measurements. Agarose gel electrophoresis experiments were also carried out to evaluate their unwinding ability towards plasmid DNA and their inhibition towards Topoisomerase I. All the results indicate that complexes 1-4 may bind more intensively to the DNA helix than does L, and intercalative binding for complexes 1-4 and electrostatic interactions for complexes 3-4 to DNA should be considered. For complex 4, covalent binding to DNA may exist. Of special note, all these metal complexes effectively inhibit Topoisomerase I even at low concentration (< or = 10 microM).
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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".