ATSE: a peptide toxicity predictor by exploiting structural and evolutionary information based on graph neural network and attention mechanism.

Journal: Briefings in bioinformatics
Published Date:

Abstract

MOTIVATION: Peptides have recently emerged as promising therapeutic agents against various diseases. For both research and safety regulation purposes, it is of high importance to develop computational methods to accurately predict the potential toxicity of peptides within the vast number of candidate peptides.

Authors

  • Lesong Wei
    Department of Computer Science, University of Tsukuba, Tsukuba, Japan, 3058577.
  • Xiucai Ye
    Department of Computer Science, University of Tsukuba, Tsukuba, Science City, Japan.
  • Yuyang Xue
    Department of Computer Science, University of Tsukuba, Tsukuba, Japan, 3058577.
  • Tetsuya Sakurai
    Department of Computer Science, University of Tsukuba, Tsukuba 3058577, Japan.
  • Leyi Wei
    School of Computer Science and Technology, Tianjin University, Tianjin, 30050, China.