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酵母中的自动正向筛选实验为含硼化合物作为 SARS-CoV-2 主蛋白酶抑制剂提供了支持。

An automated positive selection screen in yeast provides support for boron-containing compounds as inhibitors of SARS-CoV-2 main protease.

机构信息

Department of Chemistry and Molecular Biology, University of Gothenburg, Göteborg, Sweden.

Chemistry Institute, São Paulo State University, Araraquara, Brazil.

出版信息

Microbiol Spectr. 2024 Oct 3;12(10):e0124924. doi: 10.1128/spectrum.01249-24. Epub 2024 Aug 20.

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus continues to cause severe disease and deaths in many parts of the world, despite massive vaccination efforts. Antiviral drugs to curb an ongoing infection remain a priority. The virus-encoded 3C-like main protease (MPro; nsp5) is seen as a promising target. Here, with a positive selection genetic system engineered in using cleavage and release of MazF toxin as an indicator, we screened in a robotized setup small molecule libraries comprising ~2,500 compounds for MPro inhibitors. We detected eight compounds as effective against MPro expressed in yeast, five of which are characterized proteasome inhibitors. Molecular docking indicates that most of these bind covalently to the MPro catalytically active cysteine. Compounds were confirmed as MPro inhibitors in an enzymatic assay. Among those were three previously only predicted ; the boron-containing proteasome inhibitors bortezomib, delanzomib, and ixazomib. Importantly, we establish reaction conditions preserving the MPro-inhibitory activity of the boron-containing drugs. These differ from the standard conditions, which may explain why boron compounds have gone undetected in screens based on enzymatic assays. Our screening system is robust and can find inhibitors of a specific protease that are biostable, able to penetrate a cell membrane, and are not generally toxic. As a cellular assay, it can detect inhibitors that fail in a screen based on an enzymatic assay using standardized conditions, and now give support for boron compounds as MPro inhibitors. This method can also be adapted for other viral proteases.IMPORTANCEThe coronavirus disease 2019 (COVID-19) pandemic triggered the realization that we need flexible approaches to find treatments for emerging viral threats. We implemented a genetically engineered platform in yeast to detect inhibitors of the virus's main protease (MPro), a promising target to curb severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Screening molecule libraries, we identified candidate inhibitors and verified them in a biochemical assay. Moreover, the system detected boron-containing molecules as MPro inhibitors. Those were previously predicted computationally but never shown effective in a biochemical assay. Here, we demonstrate that they require a non-standard reaction buffer to function as MPro inhibitors. Hence, our cell-based method detects protease inhibitors missed by other approaches and provides support for the boron-containing molecules. We have thus demonstrated that our platform can screen large numbers of chemicals to find potential inhibitors of a viral protease. Importantly, the platform can be modified to detect protease targets from other emerging viruses.

摘要

严重急性呼吸系统综合征冠状病毒 2 (SARS-CoV-2)病毒继续在世界许多地区导致严重疾病和死亡,尽管进行了大规模疫苗接种。抑制正在进行的感染的抗病毒药物仍然是当务之急。病毒编码的 3C 样主要蛋白酶(MPro;nsp5)被视为有希望的靶标。在这里,我们使用在 中设计的带有正选择遗传系统的机器人设置,筛选了约 2500 种化合物的小分子文库,以寻找 MPro 抑制剂。我们在酵母中检测到 8 种有效抑制 MPro 的化合物,其中 5 种是蛋白酶体抑制剂。分子对接表明,大多数化合物与 MPro 的催化活性半胱氨酸共价结合。在酶促测定中证实了这些化合物是 MPro 抑制剂。其中三种是以前仅预测的硼蛋白酶体抑制剂硼替佐米、丹那佐米和伊沙佐米。重要的是,我们建立了在保留硼药物抑制 MPro 活性的条件下的反应条件。这些与标准条件不同,这可能解释了为什么基于酶促测定的筛选中未检测到硼化合物。我们的筛选系统稳健,可以找到生物稳定、能够穿透细胞膜且通常不具有毒性的特定蛋白酶抑制剂。作为细胞测定法,它可以检测在基于使用标准化条件的酶促测定的筛选中失败的抑制剂,并且现在为硼化合物作为 MPro 抑制剂提供了支持。该方法还可以适用于其他病毒蛋白酶。

重要性

2019 年冠状病毒病(COVID-19)大流行使人们意识到,我们需要灵活的方法来寻找针对新出现的病毒威胁的治疗方法。我们在酵母中实施了一种基因工程平台,以检测病毒主要蛋白酶(MPro)的抑制剂,这是抑制严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)感染的有希望的靶标。通过筛选分子文库,我们鉴定了候选抑制剂,并在生化测定中进行了验证。此外,该系统还检测到含硼分子作为 MPro 抑制剂。这些以前是通过计算预测的,但从未在生化测定中证明有效。在这里,我们证明它们需要非标准反应缓冲液才能作为 MPro 抑制剂起作用。因此,我们的细胞方法检测到其他方法错过的蛋白酶抑制剂,并为含硼分子提供支持。因此,我们已经证明,我们的平台可以筛选大量化学物质,以寻找病毒蛋白酶的潜在抑制剂。重要的是,该平台可以修改为检测来自其他新兴病毒的蛋白酶靶标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1537/11448104/ebed1991aa07/spectrum.01249-24.f001.jpg

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