Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors
Congying Pu, Hui Cui, Huaxing Yu, Xin Cheng, Man Zhang, Luoheng Qin, Zhilin Ning, Wendong Zhang, Shan Chen, Yuhang Qian, Rui Wang, Ling Wang, Xiaoxia Lin, David Gennert, Frank W. Pun, Feng Ren, Alex Zhavoronkov
Abstract
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 use several artificial intelligence techniques and patient-based multi-omics 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 leverage 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 chemotherapy in suppressing tumor growth with good tolerance. Our findings provide evidence supporting ENPP1 as an innate immune checkpoint across solid tumors and reports an AI design-aided ENPP1 inhibitor, ISM5939, as a cutting-edge STING modulator for cancer therapy, paving a path for immunotherapy advancements. While the STING-type-I interferon pathway plays a key role in anti-tumour immunity, current direct STING agonists have limited therapeutic benefit. Here, the authors identify ENPP1 as a safer and more effective STING-modulating target than direct STING agonism, and use an AI-based drug design platform to design the ENPP1-selective inhibitor ISM5939.