Artificial intelligence and big data facilitated targeted drug discovery.

Journal: Stroke and vascular neurology
Published Date: Nov 7, 2019

Abstract

Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database including detailed information of approved, investigational and withdrawn drugs, as well as other nutraceutical and metabolite structures. PubChem is a chemical compound database including all commercially available compounds as well as other synthesisable compounds. Protein Data Bank is a crystal structure database including X-ray, cryo-EM and nuclear magnetic resonance protein three-dimensional structures as well as their ligands. On the other hand, artificial intelligence (AI) is playing an important role in the drug discovery progress. The integration of such big data and AI is making a great difference in the discovery of novel targeted drug. In this review, we focus on the currently available advanced methods for the discovery of highly effective lead compounds with great absorption, distribution, metabolism, excretion and toxicity properties.

Authors

  • Benquan Liu
    Jiangsu Key Lab of Drug Screening, China Pharmaceutical University, Nanjing, China.
  • Huiqin He
    Jiangsu Key Lab of Drug Screening, China Pharmaceutical University, Nanjing, China.
  • Hongyi Luo
    Jiangsu Key Lab of Drug Screening, China Pharmaceutical University, Nanjing, China.
  • Tingting Zhang
    Department of Environmental Science and Engineering, College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, China. Electronic address: zhangtt@mail.buct.edu.cn.
  • Jingwei Jiang
    Jiangsu Key Lab of Drug Screening, China Pharmaceutical University, Nanjing, China.

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