SE(3)-equivariant ternary complex prediction towards target protein degradation.

Journal: Nature communications
Published Date: Jul 1, 2025

Abstract

Targeted protein degradation (TPD) has rapidly emerged as a powerful modality for drugging previously "undruggable" proteins. TPD employs small molecules like PROTACs and molecular glue degraders (MGD) to induce target protein degradation via the formation of a ternary complex with an E3 ligase. However, the rational design of these degraders is severely hindered by the difficulty of obtaining these ternary structures. Here we introduce DeepTernary, a novel end-to-end deep learning approach using an SE(3)-equivariant encoder and a query-based decoder to accurately and rapidly predict these critical structures. Trained on carefully curated TernaryDB, DeepTernary achieves state-of-the-art performance on PROTAC benchmarks without prior exposure to known PROTACs and shows notable prediction capability on the more challenging MGD benchmark with a blind docking protocol. Remarkably, the buried surface areas calculated from predicted structures correlate with experimental degradation potency metrics. Overall, DeepTernary offers a powerful tool for the development of targeted protein degraders.

Authors

  • Fanglei Xue
    ReLER Lab, AAII, University of Technology Sydney, Sydney, NSW, 2007, Australia.
  • Meihan Zhang
    Frontier Research Center for Cell Response, Nankai-Oxford International Advanced Research Institute, College of Life Sciences, Nankai University, Tianjin, China.
  • Shuqi Li
    School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China.
  • Xinyu Gao
    Department of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China; Tianjin Institute of Coloproctology, Tianjin, China.
  • James A Wohlschlegel
    Department of Biological Chemistry at David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
  • Wenbing Huang
    Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China.
  • Yi Yang
    Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Weixian Deng
    Department of Biological Chemistry at David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. weixiandeng@ucla.edu.

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