Nature Communications (May 2025)

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,
  • Wen Zhang,
  • Shan Chen,
  • Yuhang Qian,
  • Feng Wang,
  • Ling Wang,
  • Xiaoxia Lin,
  • David Gennert,
  • Frank W. Pun,
  • Feng Ren,
  • Alex Zhavoronkov

DOI
https://doi.org/10.1038/s41467-025-59874-0
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 23

Abstract

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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.