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Nat Biotechnol. 2019 Sep;37(9):1038-1040. doi: 10.1038/s41587-019-0224-x. Epub 2019 Sep 2.

Deep learning enables rapid identification of potent DDR1 kinase inhibitors.

Author information

1
Insilico Medicine Hong Kong Ltd, Pak Shek Kok, New Territories, Hong Kong. alex@insilico.com.
2
Insilico Medicine Hong Kong Ltd, Pak Shek Kok, New Territories, Hong Kong.
3
WuXi AppTec Co., Ltd, Shanghai, China.
4
Department of Chemistry, University of Toronto, Toronto, Ontario, Canada.
5
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
6
Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada.
7
Canadian Institute for Advanced Research, Toronto, Ontario, Canada.

Abstract

We have developed a deep generative model, generative tensorial reinforcement learning (GENTRL), for de novo small-molecule design. GENTRL optimizes synthetic feasibility, novelty, and biological activity. We used GENTRL to discover potent inhibitors of discoidin domain receptor 1 (DDR1), a kinase target implicated in fibrosis and other diseases, in 21 days. Four compounds were active in biochemical assays, and two were validated in cell-based assays. One lead candidate was tested and demonstrated favorable pharmacokinetics in mice.

PMID:
31477924
DOI:
10.1038/s41587-019-0224-x
[Indexed for MEDLINE]

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