Semi-Covariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and Its Variants Omicron, BA.5, EG.5, and JN.1 for Viral Infectivity, Virulence and Immune Escape

被引:0
|
作者
Zhu, Botao [1 ]
Lin, Huancheng [2 ]
Huang, Jun Steed [2 ]
Zhang, Wandong [3 ,4 ]
机构
[1] Western Univ, Dept Elect & Comp Engn, London, ON N6A 5B9, Canada
[2] Carleton Univ, Sch Informat Technol, Ottawa, ON K1S 5B6, Canada
[3] Natl Res Council Canada, Human Hlth Therapeut Res Ctr, 1200 Montreal Rd,Bldg M54, Ottawa, ON K1A 0R6, Canada
[4] Univ Ottawa, Fac Med, Ottawa, ON K1H 8M5, Canada
来源
VIRUSES-BASEL | 2024年 / 16卷 / 08期
关键词
SARS-CoV-2; coronaviruses; variants; spike protein sequence; semi-covariance coefficient; infectivity; virulence; immune escape;
D O I
10.3390/v16081192
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Semi-covariance has attracted significant attention in recent years and is increasingly employed to elucidate statistical phenomena exhibiting fluctuations, such as the similarity or difference in charge patterns of spike proteins among coronaviruses. In this study, by examining values above and below the average/mean based on the positive and negative charge patterns of amino acid residues in the spike proteins of SARS-CoV-2 and its current circulating variants, the proposed methods offer profound insights into the nonlinear evolving trends in those viral spike proteins. Our study indicates that the charge span value can predict the infectivity of the virus and the charge density can estimate the virulence of the virus, and both predicated infectivity and virulence appear to be associated with the capability of viral immune escape. This semi-covariance coefficient analysis may be used not only to predict the infectivity, virulence and capability of immune escape for coronaviruses but also to analyze the functionality of other viral proteins. This study improves our understanding of the trend of viral evolution in terms of viral infectivity, virulence or the capability of immune escape, which remains further validated by more future studies and statistical data.
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页数:11
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