使用AlphaFold和祖先分析对延长因子G的进化见解
Shawonur Rahaman1, Jacob H Steele2, Yi Zeng1
1Department of Chemistry, University of Houston, Houston, TX, 77204, USA.
Computers in biology and medicine
|April 13, 2025
概括
延长因子G (EF-G) 的形状灵活性塑造了蛋白质合成. 阿尔法折叠和序列分析揭示了EF-G.
科学领域:
- 分子生物学分子生物学
- 进化生物学 进化生物学
- 结构生物学 结构生物学
背景情况:
- 延长因子G (EF-G) 在蛋白质合成过程中对核糖体转移至关重要.
- 没有完全理解EF-G的形状动态和进化历史.
研究的目的:
- 调查EF-G.的构造格局和进化差异.
- 了解序列变化如何影响EF-G的形状和功能.
主要方法:
- 整合AlphaFold结构预测与基于多重序列对齐 (MSA) 的序列分析.
- 遗传学分析和祖先序列重建.
主要成果:
- 确定了野生类型EF-G的五个高度信任的结构状态,显示出比以前知道的更大的形状多样性.
- 发现交换机I循环中的单点突变会影响两个主要形状状态 (con1和con2) 之间的平衡.
- 重建的祖先EF-Gs具有降低的GTPase和转位酶活性,表明这些功能在以后进化.
结论:
- 符合性灵活性是EF-G功能和专业化的关键.
- 强大的转位酶活性在EF-G主要形态状态的分歧后演变.
- 计算管道为翻译机械的演变提供了洞察力.
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