Content area
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
Title
Deep learning enables rapid identification of potent DDR1 kinase inhibitors
Author
Zhavoronkov, Alex 1
; Ivanenkov, Yan A 1 ; Aliper, Alex 1 ; Veselov, Mark S 1 ; Aladinskiy, Vladimir A 1 ; Aladinskaya, Anastasiya V 1 ; Terentiev, Victor A 1 ; Polykovskiy, Daniil A 1 ; Kuznetsov, Maksim D 1 ; Arip Asadulaev 1 ; Volkov, Yury 1 ; Zholus, Artem 1 ; Shayakhmetov, Rim R 1 ; Zhebrak, Alexander 1 ; Minaeva, Lidiya I 1 ; Zagribelnyy, Bogdan A 1 ; Lee, Lennart H 2
; Soll, Richard 2 ; Madge, David 2 ; Li, Xing 2 ; Guo, Tao 2
; Aspuru-Guzik, Alán 3
1 Insilico Medicine Hong Kong Ltd, Pak Shek Kok, New Territories, Hong Kong
2 WuXi AppTec Co., Ltd, Shanghai, China
3 Department of Chemistry, University of Toronto, Toronto, Ontario, Canada; Department of Computer Science, University of Toronto, Toronto, Ontario, Canada; Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada; Canadian Institute for Advanced Research, Toronto, Ontario, Canada
; Ivanenkov, Yan A 1 ; Aliper, Alex 1 ; Veselov, Mark S 1 ; Aladinskiy, Vladimir A 1 ; Aladinskaya, Anastasiya V 1 ; Terentiev, Victor A 1 ; Polykovskiy, Daniil A 1 ; Kuznetsov, Maksim D 1 ; Arip Asadulaev 1 ; Volkov, Yury 1 ; Zholus, Artem 1 ; Shayakhmetov, Rim R 1 ; Zhebrak, Alexander 1 ; Minaeva, Lidiya I 1 ; Zagribelnyy, Bogdan A 1 ; Lee, Lennart H 2
; Soll, Richard 2 ; Madge, David 2 ; Li, Xing 2 ; Guo, Tao 2
; Aspuru-Guzik, Alán 3 1 Insilico Medicine Hong Kong Ltd, Pak Shek Kok, New Territories, Hong Kong
2 WuXi AppTec Co., Ltd, Shanghai, China
3 Department of Chemistry, University of Toronto, Toronto, Ontario, Canada; Department of Computer Science, University of Toronto, Toronto, Ontario, Canada; Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada; Canadian Institute for Advanced Research, Toronto, Ontario, Canada
Pages
1038-1040
Publication year
2019
Publication date
Sep 2019
ISSN
10870156
e-ISSN
15461696
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2284612926
Copyright
Copyright Nature Publishing Group Sep 2019