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

Journal: Nature communications
Published Date:

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.

Authors

  • Congying Pu
    Insilico Medicine Shanghai Ltd, 9F, Chamtime Plaza Block C, Lane 2889, Jinke Road, Pudong New Area, Shanghai, China.
  • Hui Cui
    Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, 1278 Keyuan Road, Shanghai 201203, PR China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, PR China.
  • Huaxing Yu
    Insilico Medicine Shanghai Ltd, 9F, Chamtime Plaza Block C, Lane 2889, Jinke Road, Pudong New Area, Shanghai, China.
  • Xin Cheng
    International Joint Laboratory for Embryonic Development & Prenatal Medicine Division of Histology and Embryology School of Medicine Jinan University Guangzhou China.
  • Man Zhang
    College of Business, Shanghai University of Finance and Economics, Shanghai, China.
  • Luoheng Qin
    Insilico Medicine Shanghai Ltd, 9F, Chamtime Plaza Block C, Lane 2889, Jinke Road, Pudong New Area, Shanghai, China.
  • Zhilin Ning
    Insilico Medicine Shanghai Ltd, 9F, Chamtime Plaza Block C, Lane 2889, Jinke Road, Pudong New Area, Shanghai, China.
  • Wen Zhang
    Oil Crops Research Institute, Chinese Academy of Agricultural Sciences Wuhan 430062 China peiwuli@oilcrops.cn zhangqi521x@126.com +86-27-8681-2943 +86-27-8671-1839.
  • Shan Chen
    National Academy of Economic Security, Beijing Jiaotong University, Beijing 100044, China.
  • Yuhang Qian
    School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK.
  • Feng Wang
    Department of Oncology, Binzhou Medical University Hospital, Binzhou, Shandong, China.
  • Ling Wang
    The State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, #7 Jinsui Road, Guangzhou, Guangdong 510230, China.
  • Xiaoxia Lin
    Insilico Medicine Shanghai Ltd, 9F, Chamtime Plaza Block C, Lane 2889, Jinke Road, Pudong New Area, Shanghai, China.
  • David Gennert
    Insilico Medicine US Inc,1000 Massachusetts Avenue, Suite 126, Cambridge, MA, 02138, USA.
  • Frank W Pun
    Insilico Medicine Hong Kong Ltd., Hong Kong Science and Technology Park, New Territories, Hong Kong, China.
  • Feng Ren
    Insilico Medicine Hong Kong Ltd., Hong Kong Science and Technology Park, New Territories, Hong Kong, China.
  • Alex Zhavoronkov
    Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, Maryland, USA.