QSAR モデリング・ADMET スクリーニング・分子ドッキング・分子動力学シミュレーションを統合した MCF-7 乳がん細胞阻害剤候補の探索
Using Monte Carlo-based QSAR modeling, this study predicted the anti-MCF-7 breast cancer activity of 144 naphthoquinone derivatives (1,2- and 1,4-isomers). A hybrid descriptor combining SMILES notation and hydrogen-suppressed graphs (HSG), together with the index of ideality of correlation (IIC) and correlation intensity index (CII), was employed to construct predictive models and identify activity-modulating molecular fragments. Predicted pIC values for 2,435 naphthoquinone derivatives revealed 67 compounds exceeding a pIC threshold of 6. Following ADMET filtering, 16 candidates were subjected to molecular docking against topoisomerase IIα (PDB ID: 1ZXM). Compound A14 demonstrated the highest binding affinity and maintained stable protein interactions throughout a 300 ns molecular dynamics simulation, with doxorubicin used as a reference standard. The results provide a computational framework for designing potent MCF-7 inhibitors.
Naphthoquinone derivatives were predicted to bind with high affinity to the active site of topoisomerase IIα, potentially suppressing MCF-7 breast cancer cell proliferation through enzyme inhibition.
This is basic research at the cellular or molecular level. For human application, inhalation is the most promising delivery route, but inhalation carries explosion risk and concentration matters (empirical LFL of 10%; high-concentration devices are not recommended).
See also:
https://h2-papers.org/en/papers/40850177