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Particle Smoother to Assimilate Asynchronous Movie Data of High-Speed AFM with MD Simulations
Journal of Chemical Theory and Computation ( IF 5.7 ) Pub Date : 2023-04-25 , DOI: 10.1021/acs.jctc.2c01268
Suguru Kato 1 , Shoji Takada 1 , Sotaro Fuchigami 1
Affiliation  

High-speed (HS) atomic force microscopy (AFM) can be used to observe structural dynamics of biomolecules under near-physiological conditions. In the AFM measurement, the probe tip scans an area of interest and acquires height data pixel by pixel so that the obtained AFM image contains a measurement time difference. In this study, to integrate molecular dynamics simulations with asynchronous HS-AFM movie data, we developed a particle smoother (PS) method for Bayesian data assimilation, one of the machine learning approaches, by extending the previous particle filter method. With a twin experiment with an asynchronous pseudo HS-AFM movie of a nucleosome, we found that the PS method with the pixel-by-pixel data acquisition reproduced the dynamic behavior of a nucleosome better than the previous particle filter method that ignored the data asynchronicity. We examined several frequencies of particle resampling in the PS method, and found that resampling once per one frame was optimal for reproducing the dynamic behavior. Thus, we found that the PS method with an appropriate resampling frequency is a powerful method for estimating the dynamic behavior of a target molecule from HS-AFM data with low spatiotemporal resolution.

中文翻译:

粒子平滑器通过 MD 模拟同化高速 AFM 的异步电影数据

高速(HS)原子力显微镜(AFM)可用于观察接近生理条件下生物分子的结构动力学。在AFM测量中,探针尖端扫描感兴趣的区域并逐像素采集高度数据,使得获得的AFM图像包含测量时间差。在本研究中,为了将分子动力学模拟与异步 HS-AFM 电影数据集成,我们通过扩展先前的粒子滤波方法,开发了一种用于贝叶斯数据同化的粒子平滑器(PS)方法,这是机器学习方法之一。通过对核小体的异步伪 HS-AFM 电影进行孪生实验,我们发现采用逐像素数据采集的 PS 方法比之前忽略数据异步性的粒子滤波方法更好地再现了核小体的动态行为。我们检查了 PS 方法中粒子重采样的几种频率,发现每帧重采样一次对于再现动态行为是最佳的。因此,我们发现具有适当重采样频率的 PS 方法是从低时空分辨率的 HS-AFM 数据估计目标分子动态行为的有效方法。
更新日期:2023-04-25
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