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Abstract：
With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n-distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2.
摘要：
随着SARS-CoV-2的快速进化，新菌株的出现是一个有趣的问题。本文提出了一种进化理论来分析病毒的突变，并确定导致新毒株产生的条件。我们使用基于刺突蛋白上的氨基酸突变的4个字母序列表示病毒变体，并采用n距离算法得出变体系统发育树。我们表明，理论上得出的树与病毒进化的实验数据一致。此外,我们提出了一个A-X模型，利用一组现有的突变位点(A)和一组随机产生的位点(X)，计算新菌株的出现。我们的发现表明，当X中的站点数量足够大时，足够数量的随机迭代可以预测新的宏谱系的生成。这些结果为理解SARS-CoV-2的演变提供了重要的理论基础。
