Elsevier

Drug Discovery Today

Volume 23, Issue 6, June 2018, Pages 1241-1250
Drug Discovery Today

Review
Informatics
The rise of deep learning in drug discovery

https://doi.org/10.1016/j.drudis.2018.01.039Get rights and content
Under a Creative Commons license
open access

Highlights

  • Deep learning technology has gained remarkable success.

  • We highlight the recent applications of deep learning in drug discovery research.

  • Some popular deep learning architectures are introduced in the current study.

  • Future development of deep learning in drug discovery is discussed.

Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other machine learning algorithms in areas such as image and voice recognition, natural language processing, among others. The first wave of applications of deep learning in pharmaceutical research has emerged in recent years, and its utility has gone beyond bioactivity predictions and has shown promise in addressing diverse problems in drug discovery. Examples will be discussed covering bioactivity prediction, de novo molecular design, synthesis prediction and biological image analysis.

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