Deep generative molecular design reshapes drug discovery.

Journal: Cell reports. Medicine
Published Date:

Abstract

Recent advances and accomplishments of artificial intelligence (AI) and deep generative models have established their usefulness in medicinal applications, especially in drug discovery and development. To correctly apply AI, the developer and user face questions such as which protocols to consider, which factors to scrutinize, and how the deep generative models can integrate the relevant disciplines. This review summarizes classical and newly developed AI approaches, providing an updated and accessible guide to the broad computational drug discovery and development community. We introduce deep generative models from different standpoints and describe the theoretical frameworks for representing chemical and biological structures and their applications. We discuss the data and technical challenges and highlight future directions of multimodal deep generative models for accelerating drug discovery.

Authors

  • Xiangxiang Zeng
    Department of Computer Science, Hunan University, Changsha, China.
  • Fei Wang
    Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States.
  • Yuan Luo
    Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL 60611, USA.
  • Seung-Gu Kang
    IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598USA.
  • Jian Tang
    Department of Decision Sciences HEC, Université de Montréal, Montreal, Québec, Canada.
  • Felice C Lightstone
    Biochemical and Biophysical Systems Group, Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.
  • Evandro F Fang
    Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, 1478, Lørenskog, Norway; The Norwegian Centre on Healthy Ageing (NO-Age), Oslo, Norway. Electronic address: e.f.fang@medisin.uio.no.
  • Wendy Cornell
    Healthcare & Life Sciences Research, IBM TJ Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, NY 10598, USA.
  • Ruth Nussinov
    Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick, Frederick, MD 21702, USA.
  • Feixiong Cheng
    Genomic Medicine Institute, Lerner Research Institute , Cleveland Clinic , Cleveland , Ohio 44106 , United States.