Recent Progress of Deep Learning in Drug Discovery.

Journal: Current pharmaceutical design
Published Date: Jan 1, 2021

Abstract

Deep learning, an emerging field of artificial intelligence based on neural networks in machine learning, has been applied in various fields and is highly valued. Herein, we mainly review several mainstream architectures in deep learning, including deep neural networks, convolutional neural networks and recurrent neural networks in the field of drug discovery. The applications of these architectures in molecular de novo design, property prediction, biomedical imaging and synthetic planning have also been explored. Apart from that, we further discuss the future direction of the deep learning approaches and the main challenges we need to address.

Authors

  • Feng Wang
    Department of Oncology, Binzhou Medical University Hospital, Binzhou, Shandong, China.
  • XiaoMin Diao
    College of Information Science and Engineering, Huaide College of Changzhou University, Taizhou 214500, China.
  • Shan Chang
    Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China.
  • Lei Xu
    Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.

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