Effect of charge and surface area on the cytotoxicity of cationic metallointercalation reagents
Bibliographic record
Abstract
Reaction of a series of nitrogen donor ligands (1-phenylpyrazoles, 2-phenylpyridine, benzo[h]quinoline, 1-(2′-pyridyl)indole, 1-phenylindazole, and 2-phenylindazole) with palladium(II) and platinum(II) salts gave complexes where ortho-metallation had occurred resulting in bidentate binding to the metal centres through N and C atoms. These cyclometallated products were isolated as µ-chloro dimers. Subsequent treatment of these µ-chloro dimers with chelating diamines such as 1,2-ethanediamine converted them into 14 cationic (1+) complexes. Analogous coordination mixed ligand complexes (charge 2+) were prepared by reaction of dichloro(1,2-ethanediamine-N,N′)palladium(II) with aromatic diamines such as 2-(1′-pyrazolyl)pyridine, 2,2′-bipyridine, and 1,10-phenanthroline. The complexes exhibited growth inhibitory activity against L1210 mouse leukæmia cells in vitro over a wide concentration range; in general, the cyclometallated complexes were more active than the mixed ligand complexes, although one cyclometallated organoplatinum complex was less active than the mixed ligand analogue. Substitution around the periphery of the aromatic ligands also resulted in increased activity. One complex, derived from 1-(2'-pyridyl)indole, was tested in vivo and showed no significant antitumour inhibition against P388 leukæmia at doses below toxic levels. Key words: anticancer, metallointercalator, cyclometallation, palladium, platinum, cytotoxicity.
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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".