识别刺突糖蛋白受体结合域作为COVID-19潜在候选疫苗的机器学习方法

IF 1.1 Q4 ALLERGY
Aryan Prajapati
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引用次数: 0

摘要

最近的SARS-CoV-2爆发促使人们继续努力利用不同的病毒蛋白靶点进行治疗,但在治疗和疫苗研究中,预防病毒蛋白在很大程度上失败了。在COVID-19发病机制缺乏明确临床证据的情况下,与以往大流行hcov相关的免疫系统反应进行比较可以为了解COVID-19发病机制提供线索。作者总结了COVID-19的可能起源和传播方法,以及我们目前对SARS-CoV-2已知爆发病毒的病毒基因组完整性的了解。COVID-19大流行仍然是全球卫生保健系统的一个主要关切。准确和及时识别SARS冠状病毒2 (SARS- cov -2)感染对于限制传播和开始治疗至关重要。测试程序中的金标准是实时逆转录酶聚合酶链反应(rRT-PCR)。尽管该测试具有很高的特异性和敏感性,但在有症状和/或CT扫描呈阳性的患者中出现错误阴性结果的发生率仍然是一个难题。本文分析了刺突糖蛋白的受体结合域,以期成为潜在的候选疫苗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Approach to Identify Receptor Binding Domain of Spike Glycoprotein as A Potential Vaccine Candidate for COVID-19
Recent SARS-CoV-2 outbreaks have spurred continuing efforts to exploit different viral protein targets for therapy, but preventing viral proteins, including in therapeutic and vaccine research, has largely failed. In the lack of clear clinical proof for COVID-19 pathogenesis, a comparison of previous pandemic HCoVs-related immune system reactions could provide insight into COVID-19 pathogenesis. Authors summarize the possible genesis and method of spread of COVID-19, in addition to our present understanding of the viral genome integrity of known outbreak viruses against SARS-CoV-2 in this study. The COVID-19 pandemic continues to be a major concern for health-care systems globally. Accurate and timely identification of SARS Coronavirus 2 (SARS-CoV-2) infection is crucial for limiting dissemination and commencing therapy. The gold standard among test procedures is real-time reverse-transcriptase polymerase-chain reaction (rRT-PCR). Despite the fact that this test has a high specificity and sensitivity, the incidence of erroneously negative findings in patients with symptoms and/or having a positive CT scan remains a difficulty. In this article authors analyze the receptor binding domain of spike glycoprotein to be potential vaccine candidates.
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来源期刊
CiteScore
0.60
自引率
10.00%
发文量
69
审稿时长
12 weeks
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