Department of Electrical and Computer engineering, Western University, London, ON N6A 5B9, Canada.
School of Information Technology, Carleton University, Ottawa, ON K1S 5B6, Canada.
Viruses. 2024 Jul 25;16(8):1192. doi: 10.3390/v16081192.
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.
近年来,半协方差受到了广泛关注,并被越来越多地用于阐明表现出波动的统计现象,例如冠状病毒刺突蛋白的电荷模式的相似性或差异性。在这项研究中,通过检查 SARS-CoV-2 及其当前流行变体的刺突蛋白中氨基酸残基的正电荷和负电荷模式上的平均值/均值以上和以下的值,提出的方法深入了解了这些病毒刺突蛋白中非线性演化趋势。我们的研究表明,电荷跨度值可以预测病毒的感染力,电荷密度可以估计病毒的毒力,而预测的感染力和毒力似乎都与病毒免疫逃逸的能力有关。这种半协方差系数分析不仅可用于预测冠状病毒的感染力、毒力和免疫逃逸能力,还可用于分析其他病毒蛋白的功能。本研究提高了我们对病毒感染性、毒力或免疫逃逸能力方面病毒进化趋势的认识,未来还需要更多的研究和统计数据来进一步验证。