Synthesis and Studies on Three‐Compartment Flavone‐Containing Combi‐Molecules Designed to Target EGFR, DNA, and MEK
Bibliographic record
Abstract
In order to induce a tandem targeting of EGFR, DNA, and MEK, we built complex combi-molecules containing an EGFR targeting quinazoline and an aminoethyltriazene moiety linking the entire molecule to PD98059. Two complex molecules were synthesized: one with a short aminoethyl spacer, AL232, and the other AL414 with a longer aminoethylaminoethyl spacer. AL414 was a more potent inhibitor of EGFR tyrosine kinase than AL232. Both combi-molecules blocked EGFR phosphorylation in whole cells and downregulated extracellular signaling-regulated kinases (ERK1,2). However, only AL414 was capable of inducing DNA damage. Thus, it was taken in vivo for metabolic analysis. The results showed that 3 h after injection, AL414 was hydrolyzed to an EGFR inhibitor FD105, which was further acetylated to FD105Ac, a more potent inhibitor of EGFR. The detected flavone derivative was PD98059 linked to the hydroxyalkyl moiety resulting from the decomposition of the alkyldiazonium species. Independent synthesis of the latter metabolite and further in vitro analysis showed that it was deprived of antiproliferative activity. The results in toto suggest that while AL414 is a three-compartment combi-molecule, only the EGFR and DNA targeting species can be released and the cleavage to the intact MEK inhibitor PD98059 was mitigated by the stability of the carbamate.
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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".