A new antiproliferative noscapine analogue: chemical synthesis and biological evaluation
Bibliographic record
Abstract
Noscapine, a naturally occurring opium alkaloid, is a widely used antitussive medication. Noscapine has low toxicity and recently it was also found to possess cytotoxic activity which led to the development of many noscapine analogues. In this paper we report on the synthesis and testing of a novel noscapine analogue. Cytotoxicity was assessed by MTT colorimetric assay using SKBR-3 and paclitaxel-resistant SKBR-3 breast cancer cell lines using different concentrations for both noscapine and the novel compound. Microtubule polymerization assay was used to determine the effect of the new compound on microtubules. To compare the binding affinity of noscapine and the novel compound to tubulin, we have done a fluorescence quenching assay. Finally, in silico methods using docking calculations were used to illustrate the binding mode of the new compound to α,β-tubulin. Our cytotoxicity results show that the new compound is more cytotoxic than noscapine on both SKBR-3 cell lines. This was confirmed by the stronger binding affinity of the new compound, compared to noscapine, to tubulin. Surprisingly, our new compound was found to have strong microtubule-destabilizing properties, while noscapine is shown to slightly stabilize microtubules. Our calculation indicated that the new compound has more binding affinity to the colchicine-binding site than to the noscapine site. This novel compound has a more potent cytotoxic effect on cancer cell lines than its parent, noscapine, and hence should be of interest as a potential anti-cancer drug.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".