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相关概念视频

Protein-protein Interfaces02:04

Protein-protein Interfaces

13.2K
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...
13.2K
Conserved Binding Sites01:49

Conserved Binding Sites

4.3K
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...
4.3K
Ligand Binding Sites02:40

Ligand Binding Sites

13.2K
Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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Protein Networks02:26

Protein Networks

4.1K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.1K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.9K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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通过深度学习识别14-3-3互动组结合点

Laura van Weesep1, Rıza Özçelik1,2,3, Marloes Pennings1,4

  • 1Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology Eindhoven The Netherlands l.brunsveld@tue.nl f.grisoni@tue.nl.

Digital discovery
|August 21, 2025
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概括

我们开发了一个深度学习模型, 预测14-3-3蛋白质的蛋白质结合点, 该模型达到75%的准确性,并确定了5个经过实验验证的结合点.

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科学领域:

  • 生物化学
  • 计算生物学
  • 结构生物学

背景情况:

  • 蛋白与蛋白的相互作用是生物过程和疾病的基础.
  • 鉴定蛋白质相互作用点,特别是对内在无序的蛋白质来说,仍然是一个重大挑战.
  • 14-3-3蛋白质作为细胞信号网络中的中心枢纽,使得它们的相互作用至关重要.

研究的目的:

  • 开发一个深度学习框架来预测14-3-3蛋白质的蛋白质结合点.
  • 在医学上相关的蛋白质中确定新的14-3-3结合点,包括内在的乱蛋白质.
  • 为预测14-3-3绑定网站提供一个免费的网络资源.

主要方法:

  • 对各种深度学习方法进行系统测试.
  • 开发一个集体深度学习模型用于序列绑定预测.
  • 该模型可用于300个医学相关的蛋白质序列.
  • 使用湿实验室技术对顶部预测序列进行实验验证.
  • 使用X射线结晶学和分子动力学模拟的结构分析.

主要成果:

  • 一个集体深度学习模型在预测14-3-3结合的外部序列上实现了75%的平衡精度.
  • 实验验证证了8个预测的序列中的5个的结合,分离常数 (Kd) 范围为1. 6±0. 1μM至70±5μM.
  • 在医学上相关的蛋白质中发现了新的结合点,包括那些与阿尔茨海默氏症等疾病有关的蛋白质.
  • 这项研究表明深度学习能够预测涉及内在无序蛋白质的相互作用.

结论:

  • 开发的深度学习框架有效地预测了14-3-3蛋白质的蛋白质结合点.
  • 发现的新结合点为研究蛋白质功能和治疗向提供了新的途径.
  • 这项研究强调了深度学习在解读复杂的蛋白质相互作用方面的力量.
  • 一个公开的网络工具被创建,以促进对14-3-3相互作用的进一步研究.