Enhancing the Predictive Power of Machine Learning Models through a Chemical Space Complementary DEL Screening Strategy.

Journal: Journal of medicinal chemistry
PMID: 39441849

Abstract

DNA-encoded library (DEL) technology is an effective method for small molecule drug discovery, enabling high-throughput screening against target proteins. While DEL screening produces extensive data, it can reveal complex patterns not easily recognized by human analysis. Lead compounds from DEL screens often have higher molecular weights, posing challenges for drug development. This study refines traditional DELs by integrating alternative techniques like photocross-linking screening to enhance chemical diversity. Combining these methods improved predictive performance for small molecule identification models. Using this approach, we predicted active small molecules for BRD4 and p300, achieving hit rates of 26.7 and 35.7%. Notably, the identified compounds exhibit smaller molecular weights and better modification potential compared to traditional DEL molecules. This research demonstrates the synergy between DEL and AI technologies, enhancing drug discovery.

Authors

  • Yanrui Suo
    State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Zhang Jiang Hi-Tech Park, Pudong, Shanghai 201203, China.
  • Xu Qian
    Department of Geriatric Medicine, Qilu Hospital of Shandong University, No. 107, Wenhuaxi Road, Jinan, 250012, China.
  • Zhaoping Xiong
    Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
  • Xiaohong Liu
    Department of Biopharmaceutics, School of Pharmacy, Shenyang Pharmaceutical University, Wenhua Road, Shenyang 110016, China. Electronic address: lvj221@163.com.
  • Chao Wang
    College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, China.
  • Baiyang Mu
    State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Zhang Jiang Hi-Tech Park, Pudong, Shanghai 201203, China.
  • Xinyuan Wu
    School of Photovoltaic and Renewable Energy Engineering, University of New South Wales, Kensington, NSW 2052, Australia.
  • Weiwei Lu
    Shanghai Testing & Inspection Institute for Medical Devices, Shanghai, China.
  • Meiying Cui
    B CUBE, Center for Molecular Bioengineering, Technische Universität Dresden, Dresden, Germany.
  • Jiaxiang Liu
    DEL Department, Suzhou Alphama Biotechnology Co., Ltd., Suzhou 215125,China.
  • Yujie Chen
    State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology, Sun Yat-sen University, 510275 Guangzhou, China.
  • Mingyue Zheng
    School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, UCAS, Hangzhou, Zhejiang Province, China.
  • Xiaojie Lu
    School of Medical Information, Wannan Medical College, Wuhu 241002, China.

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