Development of New N-{4-[(7-Chloro-5-methylpyrrolo[2,1-f] [1,2,4]triazin-4-yl)oxy]-3-fluorophenyl}benzenesulfonamide Analogues: Exploring Anticancer Potential through MerTK Inhibition
Bibliographic record
Abstract
Abstract Mer proto-oncogene tyrosine-protein kinase (MerTK), a part of the TAM (TYRO3, AXL, and MerTK) family, is directly correlated with metastasis and various types of cancers. The inhibition of this receptor is a promising strategy for more-effective chemotherapy. Considering the pharmacophoric features of the active domain of MerTK and the structural characteristics of the investigational drug BMS794833, we designed five new N-{4-[(7-chloro-5-methylpyrrolo[2,1-f][1,2,4]triazin-4-yl)oxy]-3-fluorophenyl}benzenesulfonamide analogues. In cytotoxicity studies, one of the analogues displayed a significantly higher cytotoxicity than cisplatin. It showed IC50 values of 2.09, 1.96, and 3.08 μM against A549, MCF-7, and MDA-MB-231 cancer cell lines, respectively. In drug metabolism and pharmacokinetic studies, it was the most stable analogue and displayed a moderate MerTK inhibitory potential. Molecular-docking studies were performed to corroborate the MerTK inhibition, and the same analogue achieved the most significant docking score (–12.33 kcal/mol). Docking interactions demonstrated that the imine and amine group of the 3-chloropyridine moiety of BMS794833 formed hydrogen bonds with the main chain of the ATP pocket residue Met674, while the oxygen atoms of the 4-oxo-1,4-dihydropyridine-3-carboxamide moiety established hydrogen bonds with the Lys619 and Asp741 amino acid residues of the allosteric pocket of MerTK protein. These promising results provide evidence that the N-{4-[(7-chloro-5-methylpyrrolo[2,1-f][1,2,4]triazin-4-yl)oxy]-3-fluorophenyl}benzenesulfonamide pharmacophore can give potential insights into the development of new MerTK inhibitors.
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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".