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识别有潜力对抗 COVID-19 的治疗药物:基于组学数据的综合方法。

Recognition of plausible therapeutic agents to combat COVID-19: An omics data based combined approach.

机构信息

Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka 1349, Bangladesh.

Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka 1349, Bangladesh; Department of Biochemistry and Microbiology, North South University, Bashundhara, Dhaka 1229, Bangladesh.

出版信息

Gene. 2021 Mar 1;771:145368. doi: 10.1016/j.gene.2020.145368. Epub 2020 Dec 17.

Abstract

Coronavirus disease-2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has become an immense threat to global public health. In this study, we performed complete genome sequencing of a SARS-CoV-2 isolate. More than 67,000 genome sequences were further inspected from Global Initiative on Sharing All Influenza Data (GISAID). Using several in silico techniques, we proposed prospective therapeutics against this virus. Through meticulous analysis, several conserved and therapeutically suitable regions of SARS-CoV-2 such as RNA-dependent RNA polymerase (RdRp), Spike (S) and Membrane glycoprotein (M) coding genes were selected. Both S and M were chosen for the development of a chimeric vaccine that can generate memory B and T cells. siRNAs were also designed for S and M gene silencing. Moreover, six new drug candidates were suggested that might inhibit the activity of RdRp. Since SARS-CoV-2 and SARS-CoV-1 have 82.30% sequence identity, a Gene Expression Omnibus (GEO) dataset of Severe Acute Respiratory Syndrome (SARS) patients were analyzed. In this analysis, 13 immunoregulatory genes were found that can be used to develop type 1 interferon (IFN) based therapy. The proposed vaccine, siRNAs, drugs and IFN based analysis of this study will accelerate the development of new treatments.

摘要

新型冠状病毒病-2019(COVID-19)由严重急性呼吸系统综合症冠状病毒-2(SARS-CoV-2)引起,已成为对全球公共卫生的巨大威胁。在本研究中,我们对 SARS-CoV-2 分离株进行了全基因组测序。从全球流感共享倡议数据(GISAID)中进一步检查了超过 67000 个基因组序列。我们使用了几种计算机技术,针对该病毒提出了有前景的治疗方法。通过细致的分析,选择了 SARS-CoV-2 的几个保守且具有治疗意义的区域,如 RNA 依赖性 RNA 聚合酶(RdRp)、刺突(S)和膜糖蛋白(M)编码基因。S 和 M 均被选作嵌合疫苗的开发,以产生记忆 B 和 T 细胞。还设计了针对 S 和 M 基因沉默的 siRNA。此外,还提出了六个可能抑制 RdRp 活性的新药物候选物。由于 SARS-CoV-2 和 SARS-CoV-1 的序列同一性为 82.30%,因此分析了严重急性呼吸系统综合症(SARS)患者的基因表达综合数据库(GEO)数据集。在此分析中,发现了 13 个免疫调节基因,可用于开发基于 I 型干扰素(IFN)的治疗方法。本研究提出的疫苗、siRNA、药物和基于 IFN 的分析将加速新疗法的开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/176b/7833977/d2b41ea4485e/gr1_lrg.jpg

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