MEGDTA: multi-modal drug-target affinity prediction based on protein three-dimensional structure and ensemble graph neural network.

Journal: BMC genomics
Published Date: Aug 11, 2025

Abstract

BACKGROUND: Drug development is a time-consuming and costly endeavor, and utilizing computer-aided methods to predict drug-target affinity (DTA) can significantly accelerate this process. The key to accurate DTA prediction lies in selecting appropriate computational models to effectively extract features from drug molecular structures and target protein structures. Existing methods usually ignore the features of the protein three-dimensional structure.

Authors

  • Zhanwei Hou
    School of Software, Henan Polytechnic University, Jiaozuo 454003, China.
  • Yijun Li
    School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Haixia Zhai
    College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454003, China.
  • Junwei Luo
    College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454003, China.
  • Yulian Ding
    Central for High Performance Computing, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China. yl.ding2@siat.ac.cn.
  • Yi Pan
    Department of Neurosis and Psychosomatic Diseases, Huzhou Third Municipal Hospital, The Affiliated Hospital of Huzhou University, Huzhou, Zhejiang, China.

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