Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Causality in Epidemiology01:21

Causality in Epidemiology

1.5K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.5K
Kinetic Energy00:23

Kinetic Energy

43.4K
Kinetic energy is the ability of an object in motion to do work or enact change. It can take on many forms. For instance, water flowing down a waterfall has kinetic energy. In biological systems, particles of light travel and are absorbed by plants to create chemical energy. Animals consume the chemical energy and give off molecules that carry their scent through the air. They also generate kinetic energy when they run away from predators. Entire systems also possess kinetic energy, like the...
43.4K
Protein-Drug Binding: Mechanism and Kinetics01:16

Protein-Drug Binding: Mechanism and Kinetics

1.8K
Protein-drug binding refers to the interaction between drugs and proteins within the body. This binding process can occur intracellularly, involving drug interactions with enzymes or receptors within cells, or extracellularly, involving plasma proteins in the blood.
Various forces drive these interactions, including hydrogen bonds, hydrophobic interactions, ionic bonds, electrostatic interactions, and van der Waals forces. These bonds enable drugs to bind to specific sites on proteins,...
1.8K
Enzyme Kinetics01:19

Enzyme Kinetics

104.0K
Enzymes speed up reactions by lowering the activation energy of the reactants. The speed at which the enzyme turns reactants into products is called the rate of reaction. Several factors impact the rate of reaction, including the number of available reactants. Enzyme kinetics is the study of how an enzyme changes the rate of a reaction.
Scientists typically study enzyme kinetics with a fixed amount of enzyme in the controlled environment of a test tube. When more reactant, or substrate, is...
104.0K
Kinetic Molecular Theory: Molecular Velocities, Temperature, and Kinetic Energy03:07

Kinetic Molecular Theory: Molecular Velocities, Temperature, and Kinetic Energy

29.8K
The kinetic molecular theory qualitatively explains the behaviors described by the various gas laws. The postulates of this theory may be applied in a more quantitative fashion to derive these individual laws.
29.8K
Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.7K
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...
2.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Detecting and quantifying overparametrization in RNA language models with REDIAL.

bioRxiv : the preprint server for biology·2026
Same author

Hierarchical AF2RAVE for Multiconformation Virtual Screening Targeting S100 Ca<sup>2+</sup>-Binding Proteins.

Journal of chemical theory and computation·2025
Same author

af2rave: protein ensemble generation with physics-based sampling.

Digital discovery·2025
Same author

Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE.

eLife·2024
Same author

Information Bottleneck Approach for Markov Model Construction.

Journal of chemical theory and computation·2024
Same author

Thermodynamically Optimized Machine-Learned Reaction Coordinates for Hydrophobic Ligand Dissociation.

The journal of physical chemistry. B·2024
Same journal

QSAR in the Browser: An Interactive Cheminformatics Web Application.

Journal of chemical information and modeling·2026
Same journal

FoldDoF: Utilizing the Primary Degrees of Freedom of Protein Backbone for Geometric Modeling and Generation.

Journal of chemical information and modeling·2026
Same journal

Derisking Affinity Optimization for Macrocycles and Cyclic Peptides: High-Precision Free Energy Simulations across Five Diverse Targets.

Journal of chemical information and modeling·2026
Same journal

An End-User Audit of Reproducibility, Data Leakage, and Overfitting of the Top-Ranked ADMET Prediction Models in TDC Leaderboards.

Journal of chemical information and modeling·2026
Same journal

PFASGroups: An Open-Source Framework for Automated Identification, Structural Classification, and Prioritization of Per- and Polyfluoroalkyl Substances.

Journal of chemical information and modeling·2026
Same journal

DeepKbhb: Context-Aware Prediction of Human Lysine β-Hydroxybutyrylation Sites.

Journal of chemical information and modeling·2026
查看所有相关文章

相关实验视频

Updated: Jan 29, 2026

Kinetic Analysis of Vasculogenesis Quantifies Dynamics of Vasculogenesis and Angiogenesis In Vitro
11:03

Kinetic Analysis of Vasculogenesis Quantifies Dynamics of Vasculogenesis and Angiogenesis In Vitro

Published on: January 31, 2018

10.1K

应用因果关系推断蛋白质动力学和动力学.

Akashnathan Aranganathan1, Eric R Beyerle2

  • 1Biophysics Program, University of Maryland, College Park, Maryland 20742, United States.

Journal of chemical information and modeling
|January 27, 2026
PubMed
概括
此摘要是机器生成的。

像AlphaFold2这样的生成模型可以预测蛋白质结构,但缺乏时间尺度. 这项研究将AlphaFold2合奏与因果模型联系起来,揭示了多个序列对齐深度如何影响蛋白质动态时间尺度.

更多相关视频

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.6K
Transcranial Magnetic Stimulation for Investigating Causal Brain-behavioral Relationships and their Time Course
11:33

Transcranial Magnetic Stimulation for Investigating Causal Brain-behavioral Relationships and their Time Course

Published on: July 18, 2014

43.9K

相关实验视频

Last Updated: Jan 29, 2026

Kinetic Analysis of Vasculogenesis Quantifies Dynamics of Vasculogenesis and Angiogenesis In Vitro
11:03

Kinetic Analysis of Vasculogenesis Quantifies Dynamics of Vasculogenesis and Angiogenesis In Vitro

Published on: January 31, 2018

10.1K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.6K
Transcranial Magnetic Stimulation for Investigating Causal Brain-behavioral Relationships and their Time Course
11:33

Transcranial Magnetic Stimulation for Investigating Causal Brain-behavioral Relationships and their Time Course

Published on: July 18, 2014

43.9K

科学领域:

  • 计算生物学是一种计算生物学.
  • 结构生物学是结构生物学.
  • 结构生物学中的机器学习

背景情况:

  • 在蛋白质数据库结构上训练的生成机器学习模型,为蛋白质构造组合采样提供了一个有前途的方法.
  • 这些模型目前缺乏关键的时间尺度和因果信息,这些信息对于理解蛋白质动态至关重要.
  • AlphaFold2是一种用于预测蛋白质结构的突出生成模型.

研究的目的:

  • 将AlphaFold2生成的结构组合与因果模型集成,以估计蛋白质构造动态时间尺度.
  • 研究多个序列对齐 (MSA) 深度和蛋白质组合中的构造波动的时间尺度之间的关系.
  • 将这种方法应用于HIV-1蛋白酶变体及其功能二次体.

主要方法:

  • 使用AlphaFold2在不同MSA深度生成的结构合集.
  • 参数化了使用AlphaFold2集的粗粒度朗格温方程的平均力潜力.
  • 结合AlphaFold2组合到因果模型中,以估计每个MSA深度的时间尺度.
  • 分析了6种HIV-1蛋白酶变体和HIV-1蛋白酶二聚体.

主要成果:

  • 证实了MSA深度和形状波动的时间尺度之间的反向关系.
  • 证明更高的MSA深度起到构造约束作用,导致更短的时间尺度.
  • 表明AlphaFold2可以探测与无偏的分子动力学模拟相似的时间尺度或比它更快的时间尺度.
  • 成功地应用了该方法来预测生物功能性HIV-1蛋白酶二聚体的动态.

结论:

  • 开发的方法成功地估计了生成模型预测的蛋白质组合的时间尺度.
  • MSA深度是影响AlphaFold2.2.预测的动态时间尺度的关键因素.
  • 该方法提供了一个框架,用于将动态纳入来自其他生成结构组合方法和共同折叠模型的预测.
  • 这些发现提供了关于HIV-1蛋白酶及其二次体的结构动态的见解.