Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors

NCOMMS-24-54326: Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appears limited. In this study, we used several artificial intelligence techniques and patient-based multi-omic data to show that Ectonucleotide Pyrophosphatase/Phosphodiesterase 1 (ENPP1), which hydrolyzes STING-activating cyclic GMP-AMP (cGAMP), is a safer and more effective STING-modulating target than direct STING agonism in multiple solid tumors. We then leveraged our generative chemistry artificial intelligence-based drug design platform to facilitate the design of ISM5939, an orally bioavailable ENPP1-selective inhibitor capable of stabilizing extracellular cGAMP and activating bystander antigen-presenting cells without inducing either toxic inflammatory cytokine release or tumor-infiltrating T-cell death. In murine syngeneic models across cancer types, ISM5939 synergizes with targeting the PD-1/PD-L1 axis and genotoxic chemotherapy in suppressing tumor growth with good tolerance. Our findings provide new evidence supporting ENPP1 as a novel innate immune checkpoint across solid tumors and reports the first AI design-aided ENPP1 inhibitor, ISM5939, as a cutting-edge STING modulator for cancer therapy, paving a new path for immunotherapy advancements. To further investigate how the tumor immune microenvironment was remodeled, tumor tissues from all groups（Vehicle, Cisplation,ISM033-154,ISM033-154-BID+Cis） were subjected to bulk RNA sequencing