Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth
Rui Zhou, Ziqian Liu, Tongtong Wu, Xianwei Pan, Tongtong Li, Kaiting Miao, Yuru Li, Xiaohui Hu, Haigang Wu, Andrew M Hemmings, Beier Jiang, Zhenzhen Zhang, Ning Liu · 2024
Read Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth by Rui Zhou, Ziqian Liu, Tongtong Wu, Xianwei Pan, Tongtong Li, Kaiting Miao, Yuru Li, Xiaohui Hu, Haigang Wu, Andrew M Hemmings, Beier Jiang, Zhenzhen Zhang, Ning Liu (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11619116.txt.
Description
Rui Zhou and twelve co-authors published a 2024 study using machine learning to find a drug against resistant lung cancer. A mutation called T790M in the EGFR gene often defeats the drug erlotinib in non-small cell lung cancer. The team screened a library of over 70,000 molecules with a Bayesian learning method for selective binding to the mutant protein. A known plant-derived compound, CDDO-Me, emerged as a strong hit.
Cell tests showed it killed mutant cancer cells, and binding assays plus simulations confirmed it grips the mutant protein. It triggered cell death and cell-cycle arrest by blocking a growth pathway, an effect cross-checked in cells with the gene knocked out. In mice bearing human tumors, the compound slowed growth in step with dose. The authors offer it as a lead against drug resistance.
Catalog record
| CREATOR | Rui Zhou, Ziqian Liu, Tongtong Wu, Xianwei Pan, Tongtong Li, Kaiting Miao, Yuru Li, Xiaohui Hu, Haigang Wu, Andrew M Hemmings, Beier Jiang, Zhenzhen Zhang, Ning Liu |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 82 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |