Biological Evaluation of Noscapine analogues as Potent and Microtubule-Targeted Anticancer Agents
Bibliographic record
Abstract
Abstract In present investigation, an attempt was undertaken to modify the C-9 position of noscapine (Nos), an opium alkaloid to yield 9 -hydroxy methyl and 9 -carbaldehyde oxime analogues for augmenting anticancer potential. The synthesis of 9-hydroxy methyl analogue of Nos was carried out by Blanc reaction and 9-carbaldehyde oxime was engineered by oxime formation method and characterized using FT-IR, 1H NMR, 13C NMR, mass spectroscopy, and so on techniques. In silico docking techniques informed that 9-hydroxy methyl and 9-carbaldehyde oxime analogues of Nos had higher binding energy score as compared to Nos. The IC50 of Nos was estimated to be 46.8 µM signficantly (P < 0.05) higher than 8.2 µM of 9-carbaldehyde oxime and 4.6 µM of 9-hydroxy methyl analogue of Nos in U87, human glioblastoma cells. Moreover, there was significant (P < 0.05) difference between the IC50 of 9-carbaldehyde oxime and 9-hydroxy methyl analogue of Nos. Consistent to in vitro cytotoxicity data, 9-hydroxy methyl analogue of Nos induced significantly (P < 0.05) higher degree of apoptosis of 84.6% in U87 cells as compared to 78.5% and 64.3% demonstrated by 9-carbaldehyde oxime and Nos, respectively. Thus the higher therapeutic efficacy of 9-hydroxy methyl analogue of Nos may be credited to higher solubility and inhibitory constant (K).
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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) | 0.002 | 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".