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蛋白质相互作用图谱鉴定出针对 SARS-CoV-2 的现有药物。

A protein interaction map identifies existing drugs targeting SARS-CoV-2.

机构信息

Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, 20090 Segrate-Milan, Milan, Italy.

Department of Physics "Giuseppe Occhialini", University of Milan-Bicocca Piazza dell'Ateneo Nuovo, 1 - 20126, Milan, Italy.

出版信息

BMC Pharmacol Toxicol. 2020 Sep 3;21(1):65. doi: 10.1186/s40360-020-00444-z.

DOI:10.1186/s40360-020-00444-z
PMID:32883368
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7470683/
Abstract

BACKGROUND

Severe acute respiratory syndrome coronavirus (SARS-CoV-2), an emerging Betacoronavirus, is the causative agent of COVID-19. Angiotensin converting enzyme 2 (ACE2), being the main cell receptor of SARS-CoV-2, plays a role in the entry of the virus into the cell. Currently, there are neither specific antiviral drugs for the treatment or preventive drugs such as vaccines.

METHODS

We proposed a bioinformatics analysis to test in silico existing drugs as a fast way to identify an efficient therapy. We performed a differential expression analysis in order to identify differentially expressed genes in COVID-19 patients correlated with ACE-2 and we explored their direct relations with a network approach integrating also drug-gene interactions. The drugs with a central role in the network were also investigated with a molecular docking analysis.

RESULTS

We found 825 differentially expressed genes correlated with ACE2. The protein-protein interactions among differentially expressed genes identified a network of 474 genes and 1130 interactions.

CONCLUSIONS

The integration of drug-gene interactions in the network and molecular docking analysis allows us to obtain several drugs with antiviral activity that, alone or in combination with other treatment options, could be considered as therapeutic approaches against COVID-19.

摘要

背景

严重急性呼吸系统综合症冠状病毒 2(SARS-CoV-2),一种新兴的贝塔冠状病毒,是 COVID-19 的病原体。血管紧张素转化酶 2(ACE2)作为 SARS-CoV-2 的主要细胞受体,在病毒进入细胞中发挥作用。目前,既没有针对 COVID-19 的特定抗病毒药物,也没有疫苗等预防性药物。

方法

我们提出了一种生物信息学分析,以测试现有药物,作为快速识别有效治疗方法的手段。我们进行了差异表达分析,以确定与 ACE-2 相关的 COVID-19 患者中差异表达的基因,并通过整合药物-基因相互作用的网络方法探索它们之间的直接关系。网络中具有核心作用的药物也通过分子对接分析进行了研究。

结果

我们发现了 825 个与 ACE2 相关的差异表达基因。差异表达基因的蛋白质-蛋白质相互作用确定了一个包含 474 个基因和 1130 个相互作用的网络。

结论

将药物-基因相互作用整合到网络中,并进行分子对接分析,使我们能够获得几种具有抗病毒活性的药物,这些药物单独或与其他治疗选择联合使用,可被视为针对 COVID-19 的治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/e884e65c9e71/40360_2020_444_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/c6efa9b2b5f0/40360_2020_444_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/2205eaa210ad/40360_2020_444_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/a123e6ebf0a6/40360_2020_444_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/e884e65c9e71/40360_2020_444_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/c6efa9b2b5f0/40360_2020_444_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/2205eaa210ad/40360_2020_444_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/a123e6ebf0a6/40360_2020_444_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b2b/7470683/e884e65c9e71/40360_2020_444_Fig4_HTML.jpg

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