1. Academic Validation
  2. Accelerated Discovery of Macrocyclic CDK2 Inhibitor QR-6401 by Generative Models and Structure-Based Drug Design

Accelerated Discovery of Macrocyclic CDK2 Inhibitor QR-6401 by Generative Models and Structure-Based Drug Design

  • ACS Med Chem Lett. 2023 Feb 8;14(3):297-304. doi: 10.1021/acsmedchemlett.2c00515.
Yang Yu 1 Junhong Huang 1 Hu He 2 Jing Han 2 Geyan Ye 1 Tingyang Xu 1 Xianqiang Sun 2 Xiumei Chen 2 Xiaoming Ren 2 Chunlai Li 2 Huijuan Li 2 Wei Huang 2 Yangyang Liu 2 Xinjuan Wang 2 Yongzhi Gao 2 Nianhe Cheng 2 Na Guo 3 Xibo Chen 3 Jianxia Feng 4 Yuxia Hua 4 Chong Liu 4 Guoyun Zhu 2 Zhi Xie 2 Lili Yao 2 Wenge Zhong 2 Xinde Chen 1 Wei Liu 1 Hailong Li 2
Affiliations

Affiliations

  • 1 Tencent AI Lab, Tencent, Shenzhen 518057, China.
  • 2 Regor Therapeutics Group, Shanghai, 201210, China.
  • 3 BioDuro-Sundia, Shanghai, 200131, China.
  • 4 BioDuro-Sundia, Beijing, 102200, China.
Abstract

Selective CDK2 inhibitors have the potential to provide effective therapeutics for CDK2-dependent cancers and for combating drug resistance due to high cyclin E1 (CCNE1) expression intrinsically or CCNE1 amplification induced by treatment of CDK4/6 inhibitors. Generative models that take advantage of deep learning are being increasingly integrated into early drug discovery for hit identification and lead optimization. Here we report the discovery of a highly potent and selective macrocyclic CDK2 Inhibitor QR-6401 (23) accelerated by the application of generative models and structure-based drug design (SBDD). QR-6401 (23) demonstrated robust antitumor efficacy in an OVCAR3 ovarian Cancer xenograft model via oral administration.

Figures
Products
  • Cat. No.
    Product Name
    Description
    Target
    Research Area
  • HY-153221
    CDK2抑制剂
    CDK