Predicting protein-ligand binding residues with deep convolutional neural networks.

Journal: BMC bioinformatics
Published Date: Feb 26, 2019

Abstract

BACKGROUND: Ligand-binding proteins play key roles in many biological processes. Identification of protein-ligand binding residues is important in understanding the biological functions of proteins. Existing computational methods can be roughly categorized as sequence-based or 3D-structure-based methods. All these methods are based on traditional machine learning. In a series of binding residue prediction tasks, 3D-structure-based methods are widely superior to sequence-based methods. However, due to the great number of proteins with known amino acid sequences, sequence-based methods have considerable room for improvement with the development of deep learning. Therefore, prediction of protein-ligand binding residues with deep learning requires study.

Authors

  • Yifeng Cui
    Faculty of Education, East China Normal University, 3663 N. Zhongshan Rd., Shanghai, 200062, China.
  • Qiwen Dong
    Institute for Data Science and Engineering, East China Normal University, Shanghai 200062, People's Republic of China.
  • Daocheng Hong
    School of Data Science & Engineering, East China Normal University, Shanghai, 3663 N. Zhongshan Rd., Shanghai, 200062, China.
  • Xikun Wang
    The High School Affiliated of Liaoning Normal University, Dalian, China.

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