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计算鉴定宿主基因组生物标志物,突出其功能、途径和调控因子,这些因素影响 SARS-CoV-2 感染和药物再利用。

Computational identification of host genomic biomarkers highlighting their functions, pathways and regulators that influence SARS-CoV-2 infections and drug repurposing.

机构信息

Bioinformatics Laboratory, Department of Statistics, Rajshahi University, Rajshahi, 6205, Bangladesh.

School of Commerce, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Toowoomba, QLD, 4350, Australia.

出版信息

Sci Rep. 2022 Mar 11;12(1):4279. doi: 10.1038/s41598-022-08073-8.

Abstract

The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world. Although, the vaccination has reduced the outspread, but people are still suffering due to the unstable RNA sequence patterns of SARS-CoV-2 which demands supplementary drugs. To explore novel drug target proteins, in this study, a transcriptomics RNA-Seq data generated from SARS-CoV-2 infection and control samples were analyzed. We identified 109 differentially expressed genes (DEGs) that were utilized to identify 10 hub-genes/proteins (TLR2, USP53, GUCY1A2, SNRPD2, NEDD9, IGF2, CXCL2, KLF6, PAG1 and ZFP36) by the protein-protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of hub-DEGs revealed some important functions and signaling pathways that are significantly associated with SARS-CoV-2 infections. The interaction network analysis identified 5 TFs proteins and 6 miRNAs as the key regulators of hub-DEGs. Considering 10 hub-proteins and 5 key TFs-proteins as drug target receptors, we performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 FDA approved drugs. We found Torin-2, Rapamycin, Radotinib, Ivermectin, Thiostrepton, Tacrolimus and Daclatasvir as the top ranked seven candidate drugs. We investigated their resistance performance against the already published COVID-19 causing top-ranked 11 independent and 8 protonated receptor proteins by molecular docking analysis and found their strong binding affinities, which indicates that the proposed drugs are effective against the state-of-the-arts alternatives independent receptor proteins also. Finally, we investigated the stability of top three drugs (Torin-2, Rapamycin and Radotinib) by using 100 ns MD-based MM-PBSA simulations with the two top-ranked proposed receptors (TLR2, USP53) and independent receptors (IRF7, STAT1), and observed their stable performance. Therefore, the proposed drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections.

摘要

COVID-19 大流行对人类生命和全球经济造成了严重破坏。尽管疫苗接种已经减少了疾病的传播,但由于 SARS-CoV-2 的 RNA 序列模式不稳定,需要补充药物,人们仍在遭受痛苦。为了探索新的药物靶标蛋白,本研究对 SARS-CoV-2 感染和对照样本的转录组 RNA-Seq 数据进行了分析。我们鉴定了 109 个差异表达基因(DEGs),并利用这些基因鉴定了 10 个关键基因/蛋白(TLR2、USP53、GUCY1A2、SNRPD2、NEDD9、IGF2、CXCL2、KLF6、PAG1 和 ZFP36)。通过蛋白质-蛋白质相互作用(PPI)网络分析。关键 DEGs 的 GO 功能和 KEGG 通路富集分析揭示了一些与 SARS-CoV-2 感染显著相关的重要功能和信号通路。互作网络分析鉴定了 5 个 TF 蛋白和 6 个 miRNA 作为关键调控因子。考虑到 10 个关键蛋白和 5 个关键 TF 蛋白作为药物靶标受体,我们对它们进行了对接分析,并与 SARS-CoV-2 3CL 蛋白酶指导的前 90 种 FDA 批准药物进行了对接分析。我们发现 Torin-2、Rapamycin、Radotinib、Ivermectin、Thiostrepton、Tacrolimus 和 Daclatasvir 是排名前七的候选药物。我们通过分子对接分析研究了它们对已发表的 COVID-19 引起的前 11 个独立和 8 个质子化受体蛋白的耐药性能,并发现它们具有很强的结合亲和力,这表明这些候选药物对最先进的替代独立受体蛋白也有效。最后,我们使用 100ns MD 基于 MM-PBSA 模拟对前三种药物(Torin-2、Rapamycin 和 Radotinib)进行了稳定性研究,并与两个排名最高的候选受体(TLR2、USP53)和独立受体(IRF7、STAT1)进行了研究,观察到它们的稳定性能。因此,这些候选药物可能在治疗不同变异的 SARS-CoV-2 感染方面发挥重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4db/8917226/56dd9e12d17f/41598_2022_8073_Fig1_HTML.jpg

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