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Deep learning enables rapid identification of potent DDR1 kinase inhibitors.

Authors :
Zhavoronkov A
Ivanenkov YA
Aliper A
Veselov MS
Aladinskiy VA
Aladinskaya AV
Terentiev VA
Polykovskiy DA
Kuznetsov MD
Asadulaev A
Volkov Y
Zholus A
Shayakhmetov RR
Zhebrak A
Minaeva LI
Zagribelnyy BA
Lee LH
Soll R
Madge D
Xing L
Guo T
Aspuru-Guzik A
Source :
Nature biotechnology [Nat Biotechnol] 2019 Sep; Vol. 37 (9), pp. 1038-1040. Date of Electronic Publication: 2019 Sep 02.
Publication Year :
2019

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.

Details

Language :
English
ISSN :
1546-1696
Volume :
37
Issue :
9
Database :
MEDLINE
Journal :
Nature biotechnology
Publication Type :
Academic Journal
Accession number :
31477924
Full Text :
https://doi.org/10.1038/s41587-019-0224-x