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病毒的爆发日期可以通过其蛋白质序列来预测

Peijun Zuo¹, Longlong Zuo², Zhihong Li³

¹School of Public Health, Shantou University, Guangdong, China. peijunzuo@hotmail.com.

Journal of translational medicine

|September 2, 2025

概括

数学模型使用一维蛋白序列预测病毒爆发时间. 这种方法分析,天花和冠状病毒菌株,根据抗原性质预测未来的疫情.

科学领域:

病毒学
计算生物学
流行病学

背景情况:

包括,天花和冠状病毒在内的病毒爆发已经发生在全球超过50年.
预测疫情爆发时间对于公共卫生准备和应对至关重要.
病原体遗传序列与疫情动态之间的关系需要进一步调查.

研究的目的:

建立一个与病毒爆发日期相关的一维蛋白序列的数学模型.
调查来自蛋白质序列的抗原性质的预测能力,以确定疫情的时间.
分析,天花和冠状病毒疫情间隔的可预测性.

主要方法:

收集了,天花和冠状病毒菌株的爆发日期.
与SARS-CoV-2 D614相关的确定的爆发时间间隔.
分析了一维抗原氨基酸序列以识别超抗原,并计算抗原精度 (x) 和酸盐含量 (y).

主要成果:

建立了一个回归方程 (z = 13. 762x2 - 109. 376x - 63.290y + 221. 197),将爆发时间间隔 (z) 与抗原精度 (x) 和酸盐含量 (y) 相对应.
该模型实现了完美的相关系数 (R = 1.0000000).
统计测试表明I类错误的概率很低 (P = 0.008).

结论:

开发的数学模型有效地使用一维蛋白序列数据预测病毒爆发日期.
这种方法适用于各种病毒,包括,天花和冠状病毒.
蛋白序列分析为预测病毒的出现和传播提供了一个有前途的工具.

关键词:

日期超越了预测的蛋白质时间序列病毒

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