Kinamycins A and C, bacterial metabolites that contain an unusual diazo group, as potential new anticancer agents: antiproliferative and cell cycle effects
Bibliographic record
Abstract
The cell growth and cell cycle inhibitory properties of the bacterial metabolites kinamycin A and kinamycin C were investigated in an attempt to determine their mechanism of action and to develop these or their analogs as anticancer agents. Both kinamycin A and kinamycin C have a highly unusual and potentially reactive diazo group. Even with short incubations, both the kinamycins were shown to have very potent cell growth inhibitory effects on either Chinese hamster ovary or K562 cells. Kinamycin C induced a rapid apoptotic response in K562 cells. The cell cycle analysis results in synchronized Chinese hamster ovary cells treated with kinamycin A revealed that they only displayed a G1/S phase block upon entry to the second cycle. Both kinamycins inhibited the catalytic decatenation activity of DNA topoisomerase IIalpha, but neither kinamycin acted as a topoisomerase II poison. Their inhibition of catalytic activity was not correlated with cell growth inhibitory effects. Pretreatment of the kinamycins with dithiothreitol protected the topoisomerase IIalpha activity, which suggested that they may be targeting critical protein sulfhydryl groups, either through reaction with the quinone or with an activated electrophilic diazo group. Neither kinamycin A nor kinamycin C intercalated into DNA, nor were they able to cross-link DNA. Although the cellular target(s) of the kinamycins has yet to be identified, the cluster map analysis, and the cell cycle and proapoptotic effects suggest that kinamycin C has a target different than other established anticancer compounds.
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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".