Application of DNA-Binding Protein Prediction Based on Graph Convolutional Network and Contact Map.

Journal: BioMed research international
Published Date: Jan 1, 2022

Abstract

DNA contains the genetic information for the synthesis of proteins and RNA, and it is an indispensable substance in living organisms. DNA-binding proteins are an enzyme, which can bind with DNA to produce complex proteins, and play an important role in the functions of a variety of biological molecules. With the continuous development of deep learning, the introduction of deep learning into DNA-binding proteins for prediction is conducive to improving the speed and accuracy of DNA-binding protein recognition. In this study, the features and structures of proteins were used to obtain their representations through graph convolutional networks. A protein prediction model based on graph convolutional network and contact map was proposed. The method had some advantages by testing various indexes of PDB14189 and PDB2272 on the benchmark dataset.

Authors

  • Weizhong Lu
    School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, China.
  • Nan Zhou
    Department of Radiology, the Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, China.
  • Yijie Ding
    School of Computer Science and Technology, Tianjin University, Tianjin 300350, China. wuxi_dyj@tju.edu.cn.
  • Hongjie Wu
    School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, China.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Qiming Fu
    School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, China.
  • Haiou Li
    Department of Computer Science and Technology, Soochow University, Suzhou, Jiangsu, 215006, China.

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