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Artificial intelligence and big data facilitated targeted drug discovery

期刊

STROKE AND VASCULAR NEUROLOGY
卷 4, 期 4, 页码 206-213

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BMJ PUBLISHING GROUP
DOI: 10.1136/svn-2019-000290

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  1. NSFC [81872892, 2018ZX09735001-004, CPU2018GY20, CPU2018GY38]

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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 DrugBank is a database including detailed information of approved, investigational and withdrawn drugs, as well as other nutraceutical and metabolite structures.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.

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