Examination of novel 4-aminoquinoline derivatives designed and synthesized by a hybrid pharmacophore approach to enhance their anticancer activities
Bibliographic record
Abstract
Abstract In an attempt to develop effective and potentially safe anticancer agents, thirty-six 4-aminoquinoline derived sulfonyl analogs were designed and synthesized using a hybrid pharmacophore approach. The cytotoxicity of these compounds was determined using three breast tumor cell lines (MDA-MB231, MDA-MB468 and MCF7) and two matching non-cancer breast epithelial cell lines (184B5 and MCF10A). Although most of the compounds were quite effective on the breast cancer cells, the compound 7-chloro-4-(4-(2,4-dinitrophenylsulfonyl)piperazin-1-yl)quinoline (13; VR23) emerged as potentially the most desirable one in this series of compounds. Data from the NCI-60 cancer panel screening show that compound 13 is effective on a wide range of different cancers. Importantly, compound 13 is needed up to 17.6-fold less doses to achieve the same IC50 against cancer than non-cancer cells (MDA-MB468 vs MCF10A), suggesting that it can potentially be less toxic to normal cells. Cancer cells formed multiple centrosomes in the presence of compound 13, resulting in the cell cycle arrest at prometa-meta phase. This abnormality leads to eventual cell demise with sub-G1 DNA content typically shown with apoptotic cells. In addition, compound 13 also causes an increase in lysosomal volume in cancer but not in non-cancer cells, which may contribute at least in part to its preferential cancer cell-killing. The cancer cell-killing effect of compound 13 is highly potentiated when combined with either bortezomib or monastrol.
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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".