Discovery of Pyrazolo[3,4-d]pyridazinone Derivatives as Selective DDR1 Inhibitors via Deep Learning Based Design, Synthesis, and Biological Evaluation-Reference-Cited by-同舟云学术

Discovery of Pyrazolo[3,4-d]pyridazinone Derivatives as Selective DDR1 Inhibitors via Deep Learning Based Design, Synthesis, and Biological Evaluation

Published:2021-11-25 Issue:1 Volume:65 Page:103-119
ISSN:0022-2623
Container-title:Journal of Medicinal Chemistry
language:en
Short-container-title:J. Med. Chem.

Author:

Tan Xiaoqin¹,Li Chunpu²,Yang Ruirui³⁴,Zhao Sen,Li Fei⁵,Li Xutong³,Chen Lifan³,Wan Xiaozhe³,Liu Xiaohong⁴,Yang Tianbiao²,Tong Xiaochu³,Xu Tingyang⁶,Cui Rongrong⁷,Jiang Hualiang²³⁴,Zhang Sulin,Liu Hong²^ORCID,Zheng Mingyue²³^ORCID

Affiliation:

1. ByteDance AI Lab, 1999 Yishan Road, Shanghai 201103, China

2. School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China

3. University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing 100049, China

4. Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, 393 Huaxiazhong Road, Shanghai 200031, China

5. Fudan University, 2005 Songhu Road, Shanghai 200433, China

6. Tencent AI Lab, Shenzhen 518057, China

7. School of Chinese Materia Medica, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing 210023, China

Funder

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Science and Technology Commission of Shanghai Municipality

National Natural Science Foundation of China

Shanghai Municipality

Tencent AI Lab

Publisher

American Chemical Society (ACS)

Subject