iNGNN-DTI: prediction of drug-target interaction with interpretable nested graph neural network and pretrained molecule models.

Journal: Bioinformatics (Oxford, England)
Published Date: Mar 4, 2024

Abstract

MOTIVATION: Drug-target interaction (DTI) prediction aims to identify interactions between drugs and protein targets. Deep learning can automatically learn discriminative features from drug and protein target representations for DTI prediction, but challenges remain, making it an open question. Existing approaches encode drugs and targets into features using deep learning models, but they often lack explanations for underlying interactions. Moreover, limited labeled DTIs in the chemical space can hinder model generalization.

Authors

  • Yan Sun
    Department of Biochemistry, Albert Einstein College of Medicine, New York, NY, United States.
  • Yan Yi Li
    Division of Biostatistics, University of Toronto, Toronto, ON, M5T 3M7, Canada.
  • Carson K Leung
    Department of Computer Science, University of Manitoba, Winnipeg, Manitoba, Canada.
  • Pingzhao Hu
    c Department of Biochemistry and Medical Genetics , University of Manitoba , Winnipeg , MB , Canada.

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