Jimmidi Ravikumar, Chamakuri Srinivas, Lu Shuo, Ucisik Melek Nihan, Chen Peng-Jen, Bohren Kurt M, Moghadasi Seyed Arad, Versteeg Leroy, Nnabuife Christina, Li Jian-Yuan, Qin Xuan, Chen Ying-Chu, Faver John C, Nyshadham Pranavanand, Sharma Kiran L, Sankaran Banumathi, Judge Allison, Yu Zhifeng, Li Feng, Pollet Jeroen, Harris Reuben S, Matzuk Martin M, Palzkill Timothy, Young Damian W
Center for Drug Discovery, Department of Pathology & Immunology, Baylor College of Medicine, Houston, Texas, 77030, USA.
Verna and Marrs McLean Department of Biochemistry and Molecular Pharmacology, Baylor College of Medicine, Houston, Texas, 77030, USA.
Commun Chem. 2023 Aug 4;6(1):164. doi: 10.1038/s42004-023-00961-y.
The development of SARS-CoV-2 main protease (M) inhibitors for the treatment of COVID-19 has mostly benefitted from X-ray structures and preexisting knowledge of inhibitors; however, an efficient method to generate M inhibitors, which circumvents such information would be advantageous. As an alternative approach, we show here that DNA-encoded chemistry technology (DEC-Tec) can be used to discover inhibitors of M. An affinity selection of a 4-billion-membered DNA-encoded chemical library (DECL) using M as bait produces novel non-covalent and non-peptide-based small molecule inhibitors of M with low nanomolar K values. Furthermore, these compounds demonstrate efficacy against mutant forms of M that have shown resistance to the standard-of-care drug nirmatrelvir. Overall, this work demonstrates that DEC-Tec can efficiently generate novel and potent inhibitors without preliminary chemical or structural information.
开发用于治疗新冠肺炎的严重急性呼吸综合征冠状病毒2(SARS-CoV-2)主要蛋白酶(M)抑制剂,大多受益于X射线结构和现有的抑制剂知识;然而,一种能避开此类信息来生成M抑制剂的有效方法将更具优势。作为一种替代方法,我们在此表明,DNA编码化学技术(DEC-Tec)可用于发现M的抑制剂。以M为诱饵对一个由40亿个成员组成的DNA编码化学文库(DECL)进行亲和筛选,产生了具有低纳摩尔K值的新型非共价、非肽基M小分子抑制剂。此外,这些化合物对已显示出对标准护理药物奈玛特韦耐药的M突变形式也有疗效。总体而言,这项工作表明DEC-Tec可以在没有初步化学或结构信息的情况下有效地生成新型强效抑制剂。