Integrating AI-Based De Novo Design with Molecular Docking and Density Functional Theory Analysis to Optimize Flavonoid Scaffolds as p53–MDM2 Inhibitors for Triple-Negative Breast Cancer
- DOI
- 10.2174/0115680266474465260825060836
- Published
- 2026-10-26
- Container
- Current Topics in Medicinal Chemistry
- Publisher
- Bentham Science Publishers Ltd.
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.2174/0115680266474465260825060836,
title = {Integrating AI-Based De Novo Design with Molecular Docking and
Density Functional Theory Analysis to Optimize Flavonoid Scaffolds as
p53–MDM2 Inhibitors for Triple-Negative Breast Cancer},
author = {Dwi Syah Fitra Ramadhan and Regina Dwi Putri Mahardika and Muli Sukmawaty and Kay Khine Soe and Tee Yee Sim and Hooi Chia Tang and Hana Chen},
year = {2026},
journal = {Current Topics in Medicinal Chemistry},
doi = {10.2174/0115680266474465260825060836},
url = {https://doi.org/10.2174/0115680266474465260825060836}
}RIS
TY - JOUR TI - Integrating AI-Based De Novo Design with Molecular Docking and Density Functional Theory Analysis to Optimize Flavonoid Scaffolds as p53–MDM2 Inhibitors for Triple-Negative Breast Cancer AU - Dwi Syah Fitra Ramadhan AU - Regina Dwi Putri Mahardika AU - Muli Sukmawaty AU - Kay Khine Soe AU - Tee Yee Sim AU - Hooi Chia Tang AU - Hana Chen PY - 2026 JO - Current Topics in Medicinal Chemistry DO - 10.2174/0115680266474465260825060836 UR - https://doi.org/10.2174/0115680266474465260825060836 ER -
APA
Ramadhan, D. S. F., Mahardika, R. D. P., Sukmawaty, M., Soe, K. K., Sim, T. Y., Tang, H. C., & Chen, H. (2026). Integrating AI-Based De Novo Design with Molecular Docking and Density Functional Theory Analysis to Optimize Flavonoid Scaffolds as p53–MDM2 Inhibitors for Triple-Negative Breast Cancer. Current Topics in Medicinal Chemistry. https://doi.org/10.2174/0115680266474465260825060836
Source records
- crossref · retrieved 2026-11-10T16:32:54.213Z