Lead optimization of novel quinolone chalcone compounds by a structure-activity relationship (SAR) study to increase efficacy and metabolic stability
Bibliographic record
Abstract
Abstract Many agents targeting the colchicine binding site in tubulin have been developed as potential anticancer agents. However, none has successfully made it to the clinic, due mainly to dose limiting toxicities and the emergence of multi-drug resistance. Chalcones targeting tubulin have been proposed as a safe and effective alternative. To identify the most effective anticancer chalcone compound, we synthesized 17 quinolone-chalcone derivatives based on our previously published CTR-17 and CTR-20, and then carried out a structure-activity relationship study. We identified two compounds, CTR-21 [((E)-8-Methoxy-3-(3-(2-methoxyphenyl)-3-oxoprop-1-enyl) quinolin-2(1H)-one)] and CTR-32 [((E)-3-(3-(2-ethoxyphenyl)-3-oxoprop-1-enyl) quinolin-2(1H)-one)] as potential leads, which contain independent moieties that play a significant role in their enhanced activities. At the nM range, CTR-21 and CTR-32 effectively kill a panel of different cancer cells originated from a variety of different tissues including breast and skin. Both compounds also effectively kill multi-drug resistant cancer cells. Most importantly, CTR-21 and CTR-32 show a very high degree of selectivity against cancer cells. In silico , both of them dock near the colchicine-binding site with similar energies. However, only CTR-21 effectively prevents tubulin polymerization, leading to the cell cycle arrest at G2/M and, eventually, cancer cell death by apoptosis. Perhaps not surprisingly, the combination of CTR-21 and ABT-737, a Bcl-2 inhibitor, showed synergistic effect in killing cancer cells, since we previously found the “parental” CTR-20 also exhibited synergism. Taken together, CTR-21 can potentially be a highly effective and relatively safe anti-cancer drug.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".