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离子液体和溶酶体促透性去污剂作为严重急性呼吸综合征冠状病毒2主蛋白酶的抑制剂:定量构效关系建模、合成及生物学测试

Ionic liquids and lysosomotropic detergents as inhibitors of the SARS-CoV-2 main protease: QSAR modeling, synthesis and biological testing.

作者信息

Hodyna Diana, Gryniukova Anastasiia, Rogalsky Sergiy, Borysko Petro, Kovalishyn Vasyl, Metelytsia Larysa

机构信息

Laboratory of Biomedical Research, V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Sciences of Ukraine, Academician Kukhar Street 1, 02094, Kyiv, Ukraine.

Laboratory of Biomedical Research, V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Sciences of Ukraine, Academician Kukhar Street 1, 02094, Kyiv, Ukraine; Bienta/Enamine Ltd., Winston Churchill Street 67, 02094, Kyiv, Ukraine.

出版信息

Biochem Biophys Res Commun. 2025 Jun 28;777:152276. doi: 10.1016/j.bbrc.2025.152276.

Abstract

SARS-CoV-2 infection is highly contagious, prompting the World Health Organization to classify it as a global public health emergency. The virus has numerous potential hosts, which complicates efforts for effective prevention, diagnosis, and treatment. Consequently, the development of innovative antiviral agents targeting SARS-CoV-2 is essential to mitigate complications and reduce mortality rates associated with COVID-19. The main protease (M), also known as 3CLpro, is a key target for drug development because of its critical role in processing viral polyproteins and its evolutionary conservation among coronaviruses, making it a promising candidate for therapeutic intervention against SARS-CoV-2. In this study, a multitask machine learning approach was employed to evaluate the antiviral effectiveness of different chemical compounds against M, using resources from the publicly available Online Chemical Database and Modeling Environment. The dataset for QSAR modeling consisted of 2844 compounds with antiviral activity measured as the EC against SARS-CoV-2 and inhibitory activity (IC) against the major protease of the virus. The predictive performance of the QSAR models was rigorously validated using both cross-validation and external test sets. Thirteen compounds, identified by the QSAR models as having high anti-M activity, were subsequently tested in vitro as protease inhibitors using a fluorescence assay. The six most active compounds were further examined through counter screening and selective screening using trypsin and papain. The highest inhibitory activity was observed in an ionic liquid derived from pyridine (16), which exhibited an IC of 25.15 μM, alongside compounds 6 and 7, which are based on imidazole, both of which demonstrated an IC of 26.2 μM. In light of the developed in silico activity model and the outcomes of the in vitro investigation of anti-M activity, these compounds are promising candidates for further research as potential anti-SARS-CoV-2 agents.

摘要

严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染具有高度传染性,促使世界卫生组织将其列为全球突发公共卫生事件。该病毒有众多潜在宿主,这使得有效预防、诊断和治疗工作变得复杂。因此,开发针对SARS-CoV-2的创新抗病毒药物对于减轻并发症和降低与2019冠状病毒病(COVID-19)相关的死亡率至关重要。主要蛋白酶(M),也称为3C样蛋白酶(3CLpro),是药物开发的关键靶点,因为它在处理病毒多聚蛋白中起关键作用,且在冠状病毒中具有进化保守性,使其成为针对SARS-CoV-2进行治疗干预的有前景的候选靶点。在本研究中,采用多任务机器学习方法,利用公开可用的在线化学数据库和建模环境中的资源,评估不同化合物对M的抗病毒效果。用于定量构效关系(QSAR)建模的数据集由2844种化合物组成,其抗病毒活性以针对SARS-CoV-2的半数有效浓度(EC)和针对该病毒主要蛋白酶的抑制活性(IC)来衡量。使用交叉验证和外部测试集对QSAR模型的预测性能进行了严格验证。QSAR模型鉴定出的13种具有高抗M活性的化合物随后作为蛋白酶抑制剂通过荧光测定法进行了体外测试。通过使用胰蛋白酶和木瓜蛋白酶进行反筛选和选择性筛选,对6种活性最高的化合物进行了进一步研究。在一种源自吡啶的离子液体(16)中观察到最高抑制活性,其IC50为25.15 μM,还有基于咪唑的化合物6和7,两者的IC50均为26.2 μM。鉴于所开发的计算机活性模型以及抗M活性的体外研究结果,这些化合物作为潜在的抗SARS-CoV-2药物有希望成为进一步研究的候选药物。

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