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相关概念视频

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

10.9K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
10.9K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K
Protein and Protein Structure02:15

Protein and Protein Structure

79.7K
Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
79.7K
Protein and Protein Structures02:15

Protein and Protein Structures

10.5K
10.5K
Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
4.2K
Protein Organization01:24

Protein Organization

6.5K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
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相关实验视频

Updated: Jul 12, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
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Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

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粗粒蛋白质力场的自上而下的机器学习

Carles Navarro1, Maciej Majewski1, Gianni De Fabritiis2,3,4

  • 1Acellera Labs, Doctor Trueta 183, 08005 Barcelona, Spain.

Journal of chemical theory and computation
|October 24, 2023
PubMed
概括

这项研究引入了一种使用神经网络和分子动力学进行蛋白质建模的新方法. 它可以有效地模拟蛋白质折叠和动态,只使用原生结构.

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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A Protocol for Computer-Based Protein Structure and Function Prediction
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相关实验视频

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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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.
  • 机器学习 机器学习

背景情况:

  • 准确的蛋白质表示对于理解蛋白质动态,折叠和相互作用至关重要.
  • 目前的方法通常需要广泛的模拟或标记数据,限制效率和可扩展性.

研究的目的:

  • 开发一种高效的粗粒蛋白质表示方法.
  • 为了能够准确地预测蛋白质折叠和动态,使用最小的数据.

主要方法:

  • 模拟使用分子动力学生成轨迹的蛋白质.
  • 通过可微分轨迹重权重定训练神经网络潜力.
  • 使用马尔科夫状态模型来预测本地类型的形状.

主要成果:

  • 该方法只需要原生蛋白质构成,不需要大量的模拟数据.
  • 训练有素的模型可以模拟蛋白质折叠事件并表现出外推能力.
  • 从粗的模拟中可以预测类似本地形状的形状.

结论:

  • 这种方法为研究蛋白质动态提供了一种可转移和数据效率高的方法.
  • 它有利于开发新的蛋白质力场和促进蛋白质科学.
  • 该方法有助于研究蛋白质折叠,动力学和长时间相互作用.