新型SARS-CoV-2包膜蛋白离子通道抑制剂的计算机检测。

IF 4.4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-06-26 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.06.036
Nina Kobe, Lennart Dreisewerd, Matic Pavlin, Polona Kogovšek, Črtomir Podlipnik, Uroš Grošelj, Miha Lukšič
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引用次数: 0

摘要

SARS-CoV-2包膜蛋白(2-EPRO)是一种对病毒发病机制至关重要的病毒蛋白,由于其高度保守且功能重要,是抗病毒药物开发的一个有希望的靶点。虽然它是治疗COVID-19的一个有希望的治疗靶点,但在以往的研究中往往被忽视。本研究对近10亿个化合物进行了高通量虚拟筛选,然后进行了严格的过滤和再对接。确定了8个得分最高、化学性质通用的候选先导化合物。在分子动力学模拟中,其中三种配体显示出稳定的蛋白质-配体复合物占据2-EPRO通道孔。其中,ZINC001799167680 (L3)和ZINC001081252239 (L2)表现出最强的结合亲和力,通过分子力学泊松-玻尔兹曼表面积分析发现,ZINC001799167680 (L3)和ZINC001081252239 (L2)在ASN15、THR11和GLU8残基上存在关键相互作用。所有配体都与已知的抑制剂金刚乙胺进行了比较,结果显示与蛋白质的结合更强。这些计算机结果突出了关注2-EPRO离子通道在新型COVID-19治疗方法开发中的潜力,并为进一步的体外和体内研究铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In silico determination of novel SARS-CoV-2 envelope protein ion channel inhibitors.

The SARS-CoV-2 envelope protein (2-EPRO), a viroporin crucial for viral pathogenesis, is a promising target for antiviral drug development as it is highly conserved and functionally important. Although it is a promising therapeutic target for the treatment of COVID-19, it has often been overlooked in previous studies. In this study, a high-throughput virtual screening of nearly one billion compounds was performed, followed by rigorous filtering and re-docking. Eight best-scoring and chemically versatile lead candidates were identified. In molecular dynamics simulations, three of these ligands showed stable protein-ligand complexes occupying the 2-EPRO channel pore. Among these, ZINC001799167680 (L3) and ZINC001081252239 (L2) exhibited the strongest binding affinity, with key interactions at residues ASN15, THR11 and GLU8 identified by Molecular Mechanics Poisson-Boltzmann Surface Area analysis. All ligands were compared with the known inhibitor rimantadine and showed stronger binding to the protein. These in silico results highlight the potential of focusing on the 2-EPRO ion channel in the development of novel COVID-19 therapeutics and pave the way for further in vitro and in vivo studies.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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