In-Silico Study of Virus-Host Protein-Protein Interactions (PPIs) can Anticipate and Cure Viruses by Reducing Time-Duration of Vaccine Trials: A Review

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Abstract

COVID-19, a pandemic, has slowed global growth. This virus' fury and fast spread necessitated worldwide drug repurposing experiments. SARS-CoV-2 surface glycoprotein triggers host innate immunological and inflammatory responses. In-silico research characterised 6VSB B as more virulent than 6VSB A and important in pathophysiology. The worldwide assessment of SARS-CoV-2 virus sequences includes analysis from hundreds of high-coverage, high-quality genomes. Protein structure prediction predicts protein three-dimensional structures using amino acid sequences. SARS-CoV-2 was examined for isoelectric point, stability, GRAVY, amino acid, and atomic composition. Protein extinction coefficients quantify light absorption at a wavelength. Sequence data can compute protein molar extinction coefficients. The present review supports in-silico investigations using an immunological and molecular biology knowledge database to create novel vaccines and determine therapeutic targets when repurposing an existing drug.
病毒-宿主蛋白-蛋白相互作用(PPIs)的计算机研究可以通过缩短疫苗试验时间来预测和治愈病毒:综述
COVID-19大流行减缓了全球经济增长。这种病毒的狂怒和快速传播需要在全球范围内进行药物再利用实验。SARS-CoV-2表面糖蛋白引发宿主先天免疫和炎症反应。芯片研究表明,6VSB B比6VSB A毒性更强,在病理生理上具有重要意义。全球对SARS-CoV-2病毒序列的评估包括对数百个高覆盖率、高质量基因组的分析。蛋白质结构预测利用氨基酸序列预测蛋白质的三维结构。检测SARS-CoV-2的等电点、稳定性、肉汁、氨基酸和原子组成。蛋白质消光系数量化一个波长的光吸收。序列数据可以计算蛋白质摩尔消光系数。本综述支持利用免疫学和分子生物学知识数据库进行计算机研究,以创造新的疫苗,并在重新利用现有药物时确定治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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