Discovery of selective and potent USP22 inhibitors via structure-based virtual screening and bioassays exerting anti-tumor activity.

Yue Zhang, Jiankun Song,Yuanzhang Zhou, Huijun Jia, Tianyu Zhou, Yingbo Sun,Qiong Gao,Yue Zhao, Yujie Pan,Zhaolin Sun,Peng Chu

Bioorganic chemistry(2023)

引用 0|浏览3
暂无评分
摘要
Ubiquitin-specific protease 22 (USP22) plays a prominent role in tumor development, invasion, metastasis and immune reprogramming, which has been proposed as a potential therapeutic target for cancer. Herein, we employed a structure-based discovery and biological evaluation and discovered that Rottlerin (IC = 2.53 μM) and Morusin (IC = 8.29 μM) and as selective and potent USP22 inhibitors. Treatment of HCT116 cells and A375 cells with each of the two compounds resulted in increased monoubiquitination of histones H2A and H2B, as well as reduced protein expression levels of Sirt1 and PD-L1, all of which are known as USP22 substrates. Additionally, our study demonstrated that the administration of Rottlerin or Morusin resulted in an increase H2Bub levels, while simultaneously reducing the expression of Sirt1 and PD-L1 in a manner dependent on USP22. Furthermore, Rottlerin and Morusin were found to enhance the degradation of PD-L1 and Sirt1, as well as increase the polyubiquitination of endogenous PD-L1 and Sirt1 in HCT116 cells. Moreover, in an in vivo syngeneic tumor model, Rottlerin and Morusin exhibited potent antitumor activity, which was accompanied by an enhanced infiltration of T cells into the tumor tissues. Using in-depth molecular dynamics (MD) and binding free energy calculation, conserved residue Leu475 and non-conserved residue Arg419 were proven to be crucial for the binding affinity and inhibitory function of USP22 inhibitors. In summary, our study established a highly efficient approach for USP22-specific inhibitor discovery, which lead to identification of two selective and potent USP22 inhibitors as potential drugs in anticancer therapy.
更多
查看译文
关键词
potent usp22 inhibitors,bioassays,structure-based,anti-tumor
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要