Cited by 1,573Computational Drug Discovery MethodsMachine Learning in Materials ScienceProtein Degradation and Inhibitors

Deep learning enables rapid identification of potent DDR1 kinase inhibitors

Zhavoronkov, Alex, Ivanenkov, Yan A., Aliper, Alex, Veselov, Mark S., Aladinskiy, Vladimir A., Aladinskaya, Anastasiya V., Terentiev, Victor A., Polykovskiy, Daniil A. +14 more·2019·Nature Biotechnology

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.

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Crossref · 10.1038/s41587-019-0224-x

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49 of 49 references verified0 citation errors · 0 not checkable

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Authors
Zhavoronkov, A., Ivanenkov, Y. A., Aliper, A., Veselov, M. S., Aladinskiy, V. A., Aladinskaya, A. V., Terentiev, V. A., Polykovskiy, D. A., Kuznetsov, M. D., Asadulaev, A., Volkov, Y., Zholus, A., Shayakhmetov, R. R., Zhebrak, A., Minaeva, L. I., Zagribelnyy, B. A., Lee, L. H., Soll, R., Madge, D., Xing, L., Guo, T., & Aspuru-Guzik, A.
Affiliations
WuXi AppTec (China) (CN)
Corresponding author
Zhavoronkov, Alex
Venue
Nature Biotechnology
Published
2019-09
Volume
37
Issue
9
Pages
1038-1040
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
OpenAlex
W2971690404
Cited by
1,573
References
57
Citations by year
2026: 320 · 2025: 306 · 2024: 224 · 2023: 178 · 2022: 169 · 2021: 206 · 2020: 144 · 2019: 22 · 2013: 1 · 2012: 1
FWCI
92.35
Type
journal article
Language
en
Open access
closed
Locations
  • Nature Biotechnology (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Nvidia
  • Nature
  • School of Medicine, University of New Mexico
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
Keywords
DDR1, deep generative models, drug discovery, fibrosis, pharmacokinetics
MeSH terms
Discoidin Domain Receptor 1, Deep Learning, Animals, Dogs, Drug Evaluation, Preclinical, Enzyme Inhibitors, Humans, Microsomes, Liver, Models, Molecular, Protein Conformation, Molecular Structure, Mice, Rats

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