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从 DNA 编码化学文库中鉴定新型 SARS-CoV-2 主蛋白酶强效抑制剂。

Identification of novel and potent inhibitors of SARS-CoV-2 main protease from DNA-encoded chemical libraries.

机构信息

Department of Medical Biochemistry and Microbiology, Zoonosis Science Center, Uppsala University, Uppsala, Sweden.

Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden.

出版信息

Antimicrob Agents Chemother. 2024 Oct 8;68(10):e0090924. doi: 10.1128/aac.00909-24. Epub 2024 Aug 28.

Abstract

screening of large compound libraries with automated high-throughput screening is expensive and time-consuming and requires dedicated infrastructures. Conversely, the selection of DNA-encoded chemical libraries (DECLs) can be rapidly performed with routine equipment available in most laboratories. In this study, we identified novel inhibitors of SARS-CoV-2 main protease (M) through the affinity-based selection of the DELopen library (open access for academics), containing 4.2 billion compounds. The identified inhibitors were peptide-like compounds containing an N-terminal electrophilic group able to form a covalent bond with the nucleophilic Cys145 of M, as confirmed by x-ray crystallography. This DECL selection campaign enabled the discovery of the unoptimized compound SLL11 (IC = 30 nM), proving that the rapid exploration of large chemical spaces enabled by DECL technology allows for the direct identification of potent inhibitors avoiding several rounds of iterative medicinal chemistry. As demonstrated further by x-ray crystallography, SLL11 was found to adopt a highly unique U-shaped binding conformation, which allows the N-terminal electrophilic group to loop back to the S1' subsite while the C-terminal amino acid sits in the S1 subsite. MP1, a close analog of SLL11, showed antiviral activity against SARS-CoV-2 in the low micromolar range when tested in Caco-2 and Calu-3 (EC = 2.3 µM) cell lines. As peptide-like compounds can suffer from low cell permeability and metabolic stability, the cyclization of the compounds will be explored in the future to improve their antiviral activity.

摘要

利用自动化高通量筛选对大型化合物库进行筛选既昂贵又耗时,并且需要专门的基础设施。相反,通过在大多数实验室都配备的常规设备,可以快速选择 DNA 编码的化学文库 (DECL)。在这项研究中,我们通过对 DELopen 文库(学术领域的开放获取)的亲和力选择,识别出了新型的 SARS-CoV-2 主蛋白酶 (M) 抑制剂。该文库包含 42 亿种化合物。通过 X 射线晶体学证实,所鉴定的抑制剂是含有 N 端亲电基团的肽样化合物,能够与 M 的亲核 Cys145 形成共价键。这次 DECL 选择活动发现了未经优化的化合物 SLL11(IC = 30 nM),证明了通过 DECL 技术快速探索大型化学空间,可以直接识别出有效的抑制剂,避免了几轮迭代的药物化学。进一步通过 X 射线晶体学证明,SLL11 采用了高度独特的 U 形结合构象,允许 N 端亲电基团在 C 端氨基酸位于 S1 亚位点的同时回环到 S1'亚位点。MP1 是 SLL11 的紧密类似物,当在 Caco-2 和 Calu-3(EC = 2.3 µM)细胞系中进行测试时,在低微摩尔范围内显示出对 SARS-CoV-2 的抗病毒活性。由于肽样化合物可能存在细胞通透性和代谢稳定性低的问题,未来将探索化合物的环化来提高其抗病毒活性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/307b/11459923/51d79c8866ad/aac.00909-24.f001.jpg

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