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时间解析的串行femtosecond晶体学数据的低通光谱分析

Cecilia M Casadei, Ahmad Hosseinizadeh¹, Spencer Bliven²

¹Department of Physics, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin 53211, USA.

Structural dynamics (Melville, N.Y.)

|June 5, 2023

概括

低通光谱分析 (LPSA) 有效地从不完整的时间解析序列女性秒结晶学 (TR-SFX) 数据中检索动态. 噪音和时机错误可能会污染结果,但改进的方法可以增强背后hodopsin 动态检索.

科学领域:

生物物理学的生物物理.
结构生物学结构生物学
计算方法计算方法

背景情况:

时间分辨率连续秒结晶学 (TR-SFX) 能够研究蛋白质动态.
分析不完整和杂的TR-SFX数据对动态检索提出了重大挑战.
低通光谱分析 (LPSA) 是一种用于动态检索的新算法.

研究的目的:

应用和评估LPSA的参数灵敏度,以实验TR-SFX数据的细菌原素 (bR).
调查TR-SFX动态检索中的高频污染源.
开发和验证一种改进的方法来处理LPSA中缺少的数据.

主要方法:

将LPSA应用于BR的实验TR-SFX数据的应用.
使用合成数据分析参数灵敏度,使用不同级别的噪音,时间不确定性和不完整性的合成数据.
开发和测试一种用于处理缺失观测的新方法.

主要成果:

在bR TR-SFX数据中发现了两种主导动态模式,其高频污染最小.
从bR数据中检索了与之前发现一致的同质化信号.
时间错误被证明会导致涂抹,但不是假元件,而高噪音水平会污染低级模式.
一种改进的数据处理方法显著增强了从合成数据中检索动态.

结论:

LPSA可以成功地从具有挑战性的TR-SFX数据集中获取生物相关的动态.
了解和减轻噪音和时间错误对于准确的动态检索至关重要.
处理缺失观测的拟议方法提高了LPSA的性能,特别是对于具有静态组件的数据.

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