AI-Driven Discovery of a Hydrophobic-Tag Degrader Targeting NSD3 for Lung Squamous Carcinoma Therapy
achieved measurable exposure and significant tumor growth inhibition in an LUSC xenograft model at 100 mg/kg with acceptable tolerability. Collectively, these results provide a practical workflow linking AI-guided ligand discovery to functional degrader development.
Authors
- Siyu Xiu (ORCID: https://orcid.org/0000-0002-1676-5900)
- Jia-Xu Zhou
- Wenyu Zhu (ORCID: https://orcid.org/0000-0003-4531-2350)
- Zhenming Liu (ORCID: https://orcid.org/0000-0002-8993-4015)
- X P
- Liangren Zhang (ORCID: https://orcid.org/0000-0002-7362-9497)
- Qi Li (ORCID: https://orcid.org/0000-0001-8776-8730)
- Xi Zhang (ORCID: https://orcid.org/0000-0002-4638-3997)
- Xiaojiao Sun
- Cheng Shi (ORCID: https://orcid.org/0000-0003-1412-9529)
- Wang Yin-yan
- Zhen-Yu Jia
- Han Wang
Institutions
- Capital University (US)
- Xinjiang Medical University (CN)
- Capital Medical University (CN)
- Peking University (CN)
- Beijing Institute of Neurosurgery (CN)
- Drug Discovery Laboratory (Norway) (NO)
- Beijing Haidian Hospital (CN)
- State Key Laboratory of Natural and Biomimetic Drugs (CN)
Publication Details
- Journal
- Journal of Medicinal Chemistry
- Published
- 2026-07-26
- DOI
- https://doi.org/10.1021/acs.jmedchem.6c00983
- Primary Topic
- Protein Degradation and Inhibitors
- Type
- article
- Field-Weighted Citation Impact
- 0.00