Discoidin domain

Novelty

Receptor tyrosine kinase

Philosophy

DDR1

Biochemistry

Theology

Biology

Kinase

Botany

Computational biology

Identification (biology)

Pharmacology

Nature Biotechnology

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. A machine learning model allows the identification of new small-molecule kinase inhibitors in days.

Deep learning enables rapid identification of potent DDR1 kinase inhibitors