Structure-based artificial intelligence-aided design of MYC-targeting degradation drugs for cancer therapy.
Journal:
Biochemical and biophysical research communications
PMID:
40288261
Abstract
The MYC protein is an oncoprotein that plays a crucial role in various cancers. Although its significance has been well recognized in research, the development of drugs targeting MYC remains relatively slow. In this study, we developed a novel MYC peptide inhibitor based on the MYC/MAX dimer structure, integrating artificial intelligence-assisted peptide drug design. Additionally, we introduced a chaperone-mediated autophagy signal to construct a MYC-targeted degradation drug, MYC-LYSO. By incorporating nano-selenium delivery, we further formulated an enhanced MYC degradation agent, Se-MYC-LYSO. Se-MYC-LYSO demonstrated potent efficacy in inducing MYC degradation, inhibiting tumor cell proliferation, and promoting apoptosis. Moreover, our findings indicate that the efficacy of Se-MYC-LYSO is dependent on the autophagy pathway. These results provide a novel strategy for targeting MYC in cancer therapy.