Multitarget Thiol-Activated Tetrapyridyl Gold(III) Complexes for Hypoxic Cancer Therapy
Bibliographic record
Abstract
Gold complexes have emerged as promising anticancer metallodrugs due to their efficient thioredoxin reductase (TrxR) inhibition, which disturbs the redox balance of cancer cells.However, in this model, the role of the ligand(s) coordinated to gold is often overlooked.In this work, we present a series of tetrapyridyl Au(III) complexes that exhibit thiol-induced release of a Au(I) ion and a tetrapyridyl ligand.The formation of a free Au(I) center is responsible for the expected TrxR inhibition.Additionally, the released ligand, which was visible in cells due to its intense blue fluorescence, showed excellent binding properties to the hERG potassium channel.Moreover, these ligands ended up in the lysosomes, resulting in significant lysosome damage.Altogether, the Au(III) complexes presented in this work showed broad-spectrum anticancer properties, both in hypoxic 2D monolayers and 3D tumor spheroids.We suggest that the interaction of the released Au(I) center and the tetrapyridyl ligand with two different protein targets may combine into prodrugs that overcome hypoxia-induced drug deactivation.
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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".