Design, Synthesis, Physicochemical, Drug-likeness Properties of Quercetin Derivatives and Their Effect On MCF-7 Cell Line and Free Radicals
Bibliographic record
Abstract
Abstract In the present study, four novel quercetin derivatives were designed and synthesised by one pot synthesis method using benzoic acid and its derivatives. The synthesised compounds were screened for physicochemical and drug-likeness properties, evaluated for in vitro antioxidant assays such as hydrogen peroxide (H2O2) and 2,2-diphenyl-1-picryl hydrazyl (DPPH), cytotoxicity study on breast cancer cell line MCF-7 and performed molecular docking against the nitric oxide synthase (iNOS) enzyme 4NOS PDB (Protein Data Bank) ID which is expressed in breast cancer. In the screening of physicochemical and drug-likeness properties, QB, QB1 and QB4 are eligible for oral drug screening and other derivatives QB2 and QB3 were not eligible for oral drug screening. Among all, QB-1 showed highest percentage of inhibition and lowest IC50 value in both the assays. The docking results displayed that QB-2 showed highest docking score and exhibited highest cytotoxicity against MCF-7 cell line and the study results conclude that QB1 and QB2 compounds can be further explored to in vivo anticancer activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".