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相关概念视频

Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

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Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
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相关实验视频

Updated: Jun 6, 2025

Myosin-Specific Adaptations of In vitro Fluorescence Microscopy-Based Motility Assays
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在生物化学过程的集体变量发现中选快速模式运动.

Donghui Shao1,2, Zhiteng Zhang1,2, Xuyang Liu1,2

  • 1Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China.

Journal of chemical theory and computation
|November 27, 2024
PubMed
概括

我们引入了一种新方法,将离散波形变换 (DWT) 与维度减小相结合,在生物分子模拟中准确识别基本集体变量 (CV),改进蛋白质动态分析.

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An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics
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Motility of Single Molecules and Clusters of Bi-Directional Kinesin-5 Cin8 Purified from S. cerevisiae Cells
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相关实验视频

Last Updated: Jun 6, 2025

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08:57

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An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics
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科学领域:

  • 计算生物学 计算生物学
  • 生物物理学的生物物理.
  • 数据科学数据科学数据科学

背景情况:

  • 集体变量 (CV) 对于分析分子动力学 (MD) 轨迹和增强采样模拟至关重要.
  • 现有的方法,如时间滞后的独立组件分析 (tICA) 和时间滞后的自动编码器 (tAE),可能会受到快速运动的阻碍,使得缓慢的自由度 (DOF) 的提取变得复杂.

研究的目的:

  • 从生物分子模拟轨迹中准确地提取缓慢的自由度 (DOF) 的新方法.
  • 改进对描述基本蛋白质动态和元稳定状态的集体变量 (CVs) 的识别.

主要方法:

  • 离散波形变换 (DWT) 与缩小维度技术 (tICA,tAE) 的整合.
  • 使用DWT来过与快速运动相对应的高频信号,以隔离缓慢的动态.
  • 然后使用tICA和tAE分析过的轨迹,以提取相关的CV.

主要成果:

  • 提议的DWT增强方法准确地识别了代表慢DOF的CV,其性能优于标准tICA和taE.
  • 对氨酸二,三和CLN025折叠的验证表明在区分转移稳定状态方面具有卓越的性能.
  • 通过DWT集成,可以提高其他CV查找算法的性能,包括Deep-tICA,从而提高采样效果.

结论:

  • 离散波形变换 (DWT) 是一种有效且计算上便宜的工具,用于预处理分子动力学轨迹.
  • 通过有效消除快速运动噪声,DWT显著提高了集体变量提取的准确性.
  • 拟议的方法提供了一个多功能和广泛适用的"免费午餐",用于改进生物分子模拟中的各种CV查找算法.