Towards a Better Understanding of the Cisplatin Mode of Action
Bibliographic record
Abstract
We have studied how platinum(II) complexes [Pt(dien)Cl]Cl, [Pt(en)Cl2] and cisplatin react with hybrid molecules that contain sulfur and nitrogen ligands, in particular Phac-Met-linker-p5'dG (Phac = phenylacetyl), Phac-His-linker-p5'dG, Phac-His-Met-linker-p5'dG and Phac-His-Gly-Met-linker-p5'dCATGGCT. The progress of the reactions was monitored by HPLC, and by [1H,15N]-HSQC NMR when 15N-cisplatin was used. The products were isolated and characterised by using enzymatic and chemical reactions and spectroscopic techniques (UV and/or NMR spectroscopy, electrospray or MALDI-TOF mass spectrometry). The combined use of digestion with proteases and reaction with hydrogen peroxide followed by mass spectrometric analysis indicated the platinum coordination positions on the peptide moiety of the largest hybrid. Monofunctional Pt-S adducts were transformed into Pt-N complexes in which Pt-N7 bonds were formed preferentially. Most of the chelates isolated had Pt-S bonds, and, in the case of cisplatin complexes, loss of the ammine trans to sulfur gave rise to the formation of tricoordinate species with platinum-mediated peptide-nucleotide cross-links. 1,2-Intrachain platinum GpG adducts were only obtained in very small amounts (1-4%).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".