机器学习由于内在无序蛋白质的酸化而导致细微的形状变化
Subinoy Adhikari1, Jagannath Mondal1
1Tata Institute of Fundamental Research, Hyderabad 500046, India.
The journal of physical chemistry. B
|October 31, 2023
概括
酸化通过改变键和相互作用微妙地改变内在无序的蛋白质 (IDP),揭示了实验测量中未见到的隐藏的构造变化. 机器学习揭示了酵母蛋白中酸化诱导的这些效应.
科学领域:
- 生物化学 生物化学
- 计算生物学 计算生物学
- 结构生物学 结构生物学
背景情况:
- 酸化显著影响内在无序的蛋白质/区域 (IDPs/IDRs),影响关键的生物功能,如细胞信号和蛋白质动态.
- 对酵母IDPs (Ash1和Sic1) 的实验研究显示,酸化后平均构造性质的变化很小.
- 了解酸化在IDP功能中的作用至关重要,但由于实验的局限性而具有挑战性.
研究的目的:
- 用先进的计算方法研究酸化的IDP中的微妙构造变化.
- 为了比较酸化对Ash1和Sic1 IDPs从*Saccharomyces cerevisiae*的构造组合的影响.
- 阐明酸化调节IDP行为的分子机制.
主要方法:
- 利用野生类型和酸化的IDP的多微秒分子动力学 (MD) 模拟.
- 开发了一个基于自编码器衍生的隐性空间维度的马尔科夫状态模型 (MSM).
- 分析了结构特征,包括接触图,二次结构,扭转角度,结和非结合相互作用.
主要成果:
- 机器学习剖析揭示了酸化后构造状态的关键相似性和差异.
- 酸化增加了键,改变了脊柱侧链键模式,并引入了盐桥.
- 观察到阴离子-π 相互作用的丧失,增加了远程疏水性接触,增强了水-蛋白相互作用.
结论:
- 机器学习与MD模拟相结合,可以有效地描述IDP中酸化诱导的构造变化.
- 酸化会导致IDP结构和动态的显著,尽管微妙的变化,这些变化不易通过大量实验测量来检测.
- 这些发现为IDP酸化的功能后果提供了关键的见解.
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