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鉴定针对 SARS-CoV-2 非结构蛋白 1(nsp1)的潜在药物。

Identification of potential drugs against SARS-CoV-2 non-structural protein 1 (nsp1).

机构信息

Núcleo Colaborativo de Biosistemas, Universidade Federal de Jataí, Jataí, GO, Brazil.

出版信息

J Biomol Struct Dyn. 2021 Sep;39(15):5657-5667. doi: 10.1080/07391102.2020.1792992. Epub 2020 Jul 13.

DOI:10.1080/07391102.2020.1792992
PMID:32657643
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7443570/
Abstract

Non-structural protein 1 (nsp1) is found in all genus, an important viral group that causes severe respiratory human diseases. This protein has significant role in pathogenesis and it is considered a probably major virulence factor. As it is absent in humans, it becomes an interesting target of study, especially when it comes to the rational search for drugs, since it increases the specificity of the target and reduces possible adverse effects that may be caused to the patient. Using approaches we seek to study the behavior of nsp1 in solution to obtain its most stable conformation and find possible drugs with affinity to all of them. For this purpose, complete model of nsp1 of SARS-CoV-2 were predicted and its stability analyzed by molecular dynamics simulations in five different replicas. After main pocket validation using two control drugs and the main conformations of nsp1, molecular docking based on virtual screening were performed to identify novel potential inhibitors from DrugBank database. It has been found 16 molecules in common to all five nsp1 replica conformations. Three of them was ranked as the best compounds among them and showed better energy score than control molecules that have activity against nsp1 from SARS-CoV-2. The results pointed out here suggest new potential drugs for therapy to aid the rational drug search against COVID-19. Communicated by Ramaswamy H. Sarma.

摘要

非结构蛋白 1(nsp1)存在于所有属中,这是一组重要的病毒属,可导致严重的人类呼吸道疾病。该蛋白在发病机制中具有重要作用,被认为是一种可能的主要毒力因子。由于它在人类中不存在,因此成为研究的有趣目标,特别是在合理寻找药物时,因为它增加了目标的特异性,并降低了可能对患者造成的不良反应。我们采用各种方法来研究 nsp1 在溶液中的行为,以获得其最稳定的构象,并寻找与所有构象都具有亲和力的可能药物。为此,我们预测了 SARS-CoV-2 的 nsp1 完整模型,并通过在五个不同副本中的分子动力学模拟来分析其稳定性。使用两种对照药物和 nsp1 的主要构象验证主要口袋后,基于虚拟筛选进行了分子对接,以从 DrugBank 数据库中识别出具有潜在亲和力的新型潜在抑制剂。在所有五个 nsp1 副本构象中都发现了 16 种共同分子。其中三种被评为最佳化合物,它们的能量评分优于针对 SARS-CoV-2 的 nsp1 的对照分子。这里指出的结果表明,有新的潜在药物可用于治疗,以辅助针对 COVID-19 的合理药物搜索。Ramaswamy H. Sarma 通讯。