Regioselective domino C–C/C–O arylation of 1,2,3-triiodobenzenes and 1,3-diketones: Synthesis and in silico evaluation of 7-iodobenzo[b]furan as potential ALK inhibitors
Bibliographic record
Abstract
We report a simple, direct, and regioselective protocol for the synthesis of 2,3-disubstituted 7-iodobenzo[b]furans via domino double C-C/C-O arylations of 1,2,3-triiodobenzene and 1,3-dicarbonyl compounds. Remarkably, the C-arylation occurred exclusively at the terminal positions, which are the most reactive and least sterically hindered. The O-arylation reactions were selectively performed with the more reactive carbonyl group. This domino process demonstrated excellent substrate tolerance. Under optimized conditions, the reaction of electron-deficient 1,2,3-triiodoarenes with dicarbonyl compounds afforded the highest isolated yields. Furthermore, the designed novel compounds were screened against ALK, revealing that among the 17 tested, ALK-9p, ALK-9b, ALK-9n, and ALK-9m exhibited the best docking scores using the extra-precision docking method. Molecular simulations of these compounds with ALK confirmed their stable binding behavior, compact topology, and minimal residue flexibility. Finally, binding free energy calculations using MM/PBSA and MM/GBSA methods further validated the pharmacological potential of these shortlisted hits as ALK inhibitors. These results demand prompt experimental validation to determine the promising clinical applications of these compounds in the management of cancer. Other Information Published in: Journal of Organometallic Chemistry License: http://creativecommons.org/licenses/by/4.0/ See article on publisher's website: https://dx.doi.org/10.1016/j.jorganchem.2025.123526
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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) | 0.001 | 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".