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首页> 外文期刊>Journal of Pharmaceutical Analysis >Structural elucidation of SARS-CoV-2 vital proteins: Computational methods reveal potential drug candidates against main protease, Nsp12 polymerase and Nsp13 helicase
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Structural elucidation of SARS-CoV-2 vital proteins: Computational methods reveal potential drug candidates against main protease, Nsp12 polymerase and Nsp13 helicase

机译:SARS-COV-2重要蛋白的结构阐明:计算方法揭示针对主要蛋白酶,NSP12聚合酶和NSP13螺旋酶的潜在药物候选物

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Recently emerged SARS-CoV-2 caused a major outbreak of coronavirus disease 2019 (COVID-19) and instigated a widespread fear, threatening global health safety. To date, no licensed antiviral drugs or vaccines are available against COVID-19 although several clinical trials are under way to test possible therapies. During this urgent situation, computational drug discovery methods provide an alternative to tiresome high-throughput screening, particularly in the hit-to-lead-optimization stage. Identification of small molecules that specifically target viral replication apparatus has indicated the highest potential towards antiviral drug discovery. In this work, we present potential compounds that specifically target SARS-CoV-2 vital proteins, including the main protease, Nsp12 RNA polymerase and Nsp13 helicase. An integrative virtual screening and molecular dynamics simulations approach has facilitated the identification of potential binding modes and favourable molecular interaction profile of corresponding compounds. Moreover, the identification of structurally important binding site residues in conserved motifs located inside the active site highlights relative importance of ligand binding based on residual energy decomposition analysis. Although the current study lacks experimental validation, the structural information obtained from this computational study has paved way for the design of targeted inhibitors to combat COVID-19 outbreak.Graphical abstractDownload : Download high-res image (326KB)Download : Download full-size image
机译:最近出现的SARS-COV-2引起了2019年冠状病毒疾病的重大爆发(Covid-19)并煽动着广泛的恐惧,威胁到威胁全球健康安全。迄今为止,虽然正在进行几种临床试验以测试可能的疗法,但没有持牌抗病毒药物或疫苗可用于Covid-19。在这种迫切的情况下,计算药物发现方法提供了令人厌倦的高通量筛选的替代方案,特别是在命中率优化阶段。鉴定特异性靶向病毒复制装置的小分子表明了抗病毒药物发现的最高潜力。在这项工作中,我们提出了专门针对SARS-COV-2重要蛋白的潜在化合物,包括主要蛋白酶,NSP12 RNA聚合酶和NSP13螺旋酶。一体化虚拟筛选和分子动力学模拟方法已经促进了相应化合物的潜在结合模式和有利的分子相互作用谱的识别。此外,位于活性位点内的保守基序中的结构重要结合位点残基的鉴定突出了基于残留能量分解分析的配体结合的相对重要性。虽然目前的研究缺乏实验验证,但从该计算研究中获得的结构信息已经为目标抑制剂设计的结构信息铺平了对抗Covid-19爆发的靶向抑制剂。绘图抽象:下载高分辨率图像(326KB)下载:下载全尺寸图像

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