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首页> 外文期刊>Medicinal chemistry >Pharmacophore-Based Virtual Screening for Identification of Novel Neuraminidase Inhibitors and Verification of Inhibitory Activity by Molecular Docking
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Pharmacophore-Based Virtual Screening for Identification of Novel Neuraminidase Inhibitors and Verification of Inhibitory Activity by Molecular Docking

机译:基于药理学的虚拟筛选,用于鉴定新型神经氨酸酶抑制剂并通过分子对接验证抑制活性

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摘要

Oseltamivir and Zanamivir are two of the recently licensed neuraminidase inhibitors used for the treatment of influenza. However, alternative antiviral agents are needed due to the development of resistant mutations in Oseltamivir subtype H1N1 and H5N1 avian influenza A viruses, the latter being a highly pathogenic avian virus that can be transferred to humans upon immediate contact with H5N1 infected poultry or surface. Novel drug inhibiting group 1 neuraminidases may potentially be developed through addition of extra substituent moieties to existing inhibitor skeletons. Another approach involves virtual screening of existing inhibitor skeletons which we have reported using novel ligands of H5N1 via virtual screening approach. In this study, we have used 3D structure of avian influenza virus H5N1 neuraminidase as target against a ligand dataset of four known neuraminidase inhibitors for in silico analysis. Using the dataset of known four inhibitors, a pharmacophore model was developed using ligand-based pharmacophore modeling strategy. This pharmacophore model was then used for virtual screening of natural compounds library taken from Princeton database. New hits that shared features of our pharmacophore model and binding interactions with receptor residues have been reported in this study. As more antiviral agents are required, the reported hits in our study may play an important role as novel antiviral agents against influenza virus.
机译:Oseltamivir和Zanamivir是最近被许可用于治疗流感的两种神经氨酸酶抑制剂。但是,由于在Oseltamivir亚型H1N1和H5N1禽流感A型病毒中产生抗性突变,因此需要其他抗病毒药,后者是一种高致病性禽流感病毒,可以在与H5N1感染的家禽或禽类表面立即接触后转移给人类。通过向现有抑制剂骨架中添加额外的取代基部分,可能会开发出新的抑制药物的第1组神经氨酸酶。另一种方法涉及对现有抑制剂骨架的虚拟筛选,我们已经报道通过虚拟筛选方法使用H5N1的新型配体。在这项研究中,我们已使用禽流感病毒H5N1神经氨酸酶的3D结构作为目标,针对四种已知的神经氨酸酶抑制剂的配体数据集进行了计算机分析。使用已知的四种抑制剂的数据集,使用基于配体的药效团建模策略开发了药效团模型。然后将该药效团模型用于从普林斯顿数据库中提取的天然化合物库的虚拟筛选。这项研究报道了共享我们药效团模型特征以及与受体残基的结合相互作用的新产品。由于需要更多的抗病毒剂,因此在我们的研究中,作为抗流感病毒的新型抗病毒剂,报道的命中数据可能起重要作用。

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