Computation-driven discovery of novel chromone derivatives for the treatment of triple-negative breast cancer via mTOR-targeted inhibition and triggering antitumor immunity

Triple-negative breast cancer (TNBC) is a highly aggressive and heterogeneous subtype of breast cancer characterized by early metastasis, poor prognosis, and high recurrence rates. Targeting dysregulated PI3K/Akt/mTOR signaling and triggering anti-tumor immunity represent promising strategies for TNBC therapy. In this study, we report the discovery of a series of novel chromone derivatives as potent mTOR inhibitors by artificial intelligence-assisted drug design and structure-based drug design. The optimal compound, MT-44 , was a highly selective mTOR inhibitor and showed no obvious binding activity to a broad panel of 200 kinases, and it exhibited nanomolar-level mTOR inhibitory and anti-TNBC cells proliferative activities. MT-44 effectively blocked the PI3K/Akt/mTOR signaling pathway and exerted robust anti-tumor efficacy in an MDA-MB-231 xenograft mouse model. Furthermore, MT-44 activated pattern recognition receptor TLR2 and upregulated the cGAS/STING signaling pathway, and reshaped the tumor microenvironment, thereby enhancing the tumor immune landscape. Collectively, our findings highlighted MT-44 as a highly selective and potent mTOR inhibitor with dual-targeted therapeutic and immunomodulatory effects, offering an appealing strategy for TNBC. The highly selective and potent mTOR inhibitor MT-44 was developed by artificial intelligence-assisted drug design and structure-based drug design. MT-44 exerted robust antitumor efficacy via mTOR protein-targeted inhibition and triggering of antitumor immunity.