Is the Reactivity of M(II)−Arene Complexes of 3-Hydroxy-2(1<i>H</i>)-pyridones to Biomolecules the Anticancer Activity Determining Parameter?
Bibliographic record
Abstract
Hydroxypyr(id)ones are versatile ligands for the synthesis of organometallic anticancer agents, equipping them with fine-tunable pharmacological properties. Herein, we report on the preparation, mode of action, and in vitro anticancer activity of Ru(II)- and Os(II)-arene complexes with alkoxycarbonylmethyl-3-hydroxy-2-pyridone ligands. The hydrolysis and binding to amino acids proceed quickly, as characterized by NMR spectroscopy and ESI mass spectrometry. However, the reaction with amino acids causes cleavage of the pyridone ligands from the metal center because the amino acids act as multidentate ligands. A similar behavior was also observed during the reactions with the model proteins ubiquitin and cytochrome c, yielding mainly [protein + M(eta(6)-p-cymene)] adducts (M = Ru, Os). Notably the ligand cleavage of the Os derivative was significantly slower than of its Ru analogue, which could explain its higher activity in in vitro anticancer assays. Furthermore, the reaction of the compounds to 5'-GMP was characterized and coordination to the N7 of the guanine moiety was demonstrated by (1)H NMR spectroscopy and X-ray diffraction analysis. CDK2/Cyclin A protein kinase inhibition studies revealed potent activity of the Ru and Os complexes.
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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".