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使用深度生成模型设计和合成具有理想药效团的 DDR1 抑制剂。

Design and Synthesis of DDR1 Inhibitors with a Desired Pharmacophore Using Deep Generative Models.

机构信息

Institute for Theoretical Medicine, Inc., 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa, 251-0012, Japan.

INTAGE Healthcare, Inc., 79, Kankoboko-cho, Shimogyo-ku, Kyoto, 600-8009, Japan.

出版信息

ChemMedChem. 2021 Mar 18;16(6):955-958. doi: 10.1002/cmdc.202000786. Epub 2021 Jan 15.

Abstract

Discoidin domain receptor 1 (DDR1) inhibitors with a desired pharmacophore were designed using deep generative models (DGMs). DDR1 is a receptor tyrosine kinase activated by matrix collagens and implicated in diseases such as cancer, fibrosis and hypoxia. Herein we describe the synthesis and inhibitory activity of compounds generated from DGMs. Three compounds were found to have sub-micromolar inhibitory activity. The most potent of which, compound 3 (N-(4-chloro-3-((pyridin-3-yloxy)methyl)phenyl)-3-(trifluoromethyl)benzamide), had an IC value of 92.5 nM. Furthermore, these compounds were predicted to interact with DDR1, which have a desired pharmacophore derived from a known DDR1 inhibitor. The results of synthesis and experiments indicated that our de novo design strategy is practical for hit identification and scaffold hopping.

摘要

使用深度生成模型(DGM)设计了具有理想药效团的 discoidin 结构域受体 1(DDR1)抑制剂。DDR1 是一种受基质胶原激活的受体酪氨酸激酶,与癌症、纤维化和缺氧等疾病有关。本文描述了从 DGM 生成的化合物的合成和抑制活性。发现三种化合物具有亚微摩尔抑制活性。其中最有效的化合物 3(N-(4-氯-3-((吡啶-3-基氧基)甲基)苯基)-3-(三氟甲基)苯甲酰胺),IC 值为 92.5 nM。此外,这些化合物被预测与 DDR1 相互作用,该蛋白具有来自已知 DDR1 抑制剂的理想药效团。合成和实验结果表明,我们的从头设计策略对于命中鉴定和支架跳跃是实用的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef9f/8048584/d1066cac1291/CMDC-16-955-g005.jpg

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