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A protein sequence-based deep transfer learning framework for identifying human proteome-wide deubiquitinase-substrate interactions

Author

Listed:
  • Yuan Liu

    (Beijing Institute of Lifeomics)

  • Dianke Li

    (Beijing Institute of Lifeomics
    China Agricultural University)

  • Xin Zhang

    (Beijing Institute of Lifeomics)

  • Simin Xia

    (Beijing Institute of Lifeomics
    Anhui Medical University)

  • Yingjie Qu

    (Beijing Institute of Lifeomics)

  • Xinping Ling

    (Beijing Institute of Lifeomics
    Hebei University)

  • Yang Li

    (Beijing Institute of Lifeomics)

  • Xiangren Kong

    (Beijing Institute of Lifeomics)

  • Lingqiang Zhang

    (Beijing Institute of Lifeomics)

  • Chun-Ping Cui

    (Beijing Institute of Lifeomics)

  • Dong Li

    (Beijing Institute of Lifeomics)

Abstract

Protein ubiquitination regulates a wide range of cellular processes. The degree of protein ubiquitination is determined by the delicate balance between ubiquitin ligase (E3)-mediated ubiquitination and deubiquitinase (DUB)-mediated deubiquitination. In comparison to the E3-substrate interactions, the DUB-substrate interactions (DSIs) remain insufficiently investigated. To address this challenge, we introduce a protein sequence-based ab initio method, TransDSI, which transfers proteome-scale evolutionary information to predict unknown DSIs despite inadequate training datasets. An explainable module is integrated to suggest the critical protein regions for DSIs while predicting DSIs. TransDSI outperforms multiple machine learning strategies against both cross-validation and independent test. Two predicted DUBs (USP11 and USP20) for FOXP3 are validated by “wet lab” experiments, along with two predicted substrates (AR and p53) for USP22. TransDSI provides new functional perspective on proteins by identifying regulatory DSIs, and offers clues for potential tumor drug target discovery and precision drug application.

Suggested Citation

  • Yuan Liu & Dianke Li & Xin Zhang & Simin Xia & Yingjie Qu & Xinping Ling & Yang Li & Xiangren Kong & Lingqiang Zhang & Chun-Ping Cui & Dong Li, 2024. "A protein sequence-based deep transfer learning framework for identifying human proteome-wide deubiquitinase-substrate interactions," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48446-3
    DOI: 10.1038/s41467-024-48446-3
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    References listed on IDEAS

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    1. Jingdong Cheng & Huirong Yang & Jian Fang & Lixiang Ma & Rui Gong & Ping Wang & Ze Li & Yanhui Xu, 2015. "Molecular mechanism for USP7-mediated DNMT1 stabilization by acetylation," Nature Communications, Nature, vol. 6(1), pages 1-11, November.
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