The Institute of Scientific and Industrial Research, Osaka University


LAST UPDATE 2021/06/15

  • 研究者氏名
    Researcher Name

    山下泰信 Yasunobu YAMASHIATA
    助教 Assistant Professor
  • 所属
    Professional Affiliation

    The Institute of Scientific and Industrial Research, Osaka University

    Department of complex molecular chemistry
  • 研究キーワード
    Research Keywords

    Medicinal Chemistry
    Organic Chemistry
Research Subject
Development of activity predictor using deep learning and its application

研究の背景 Background


Machine learning has been successful in many fields, but no general methodology has yet been established in the medicinal field. This reason is that it is necessary to select a descriptor based on the experience of researchers to input of chemical structures. Therefore, drug screening using deep learning, which allows AI itself to learn the entire compound is focused.

研究の目標 Outcome


The purpose of this research is to develop a drug discovery methodology that predicts highly active compounds using deep learning, and to discover bioactive substances with a novel structure. In this research, deep learning is utilized to input the chemical structure itself without the process of converting structural formulas to descriptors, enabling the AI ​​itself to learn the entire compound.

研究図Research Figure

Fig.1. Schematic representation of protein-compound binding prediction.

Fig.2. Deep learning approach to new drug candidate

文献 / Publications

ChemBioChem, 2020, 21, 1968.; Bioorg. Med. Chem., 2019, 27, 3339.; Synthesis, 2019, 51, 1178.; Mol. Inf., 2018, 37, 1700120.; Biosci. Biotechnol. Biochem., 2017, 81, 1279.; Heterocycles, 2017, 95, 370.; Synthesis, 2016, 48, 2191.; Chem. Pharm. Bull., 2016, 64, 961