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相关概念视频

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...
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Ligand Binding Sites02:40

Ligand Binding Sites

12.8K
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...
12.8K
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
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.8K
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...
4.8K
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

12.8K
The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
12.8K
Induced-fit Model01:13

Induced-fit Model

80.6K
Most chemical reactions in cells require enzymes—biological catalysts that speed up the reaction without being consumed or permanently changed. They reduce the activation energy needed to convert the reactants into products. Enzymes are proteins, that usually work by binding to a substrate—a reactant molecule that they act upon.
Enzymes exhibit substrate specificity, meaning that they can only bind to certain substrates. This is mainly determined by the shape and chemical...
80.6K

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相关实验视频

Updated: Jun 18, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

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基于结构信息的机器学习辅助基质结合口袋工程.

Xinglong Wang1,2,3, Kangjie Xu3, Xuan Zeng4

  • 1School of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China.

Briefings in bioinformatics
|August 5, 2024
PubMed
概括

一个新的3D深度学习模型准确地预测了酶基质结合部位,这对酶工程至关重要. 这种方法增强了酶活性预测,并指导向突变以改善催化功能.

关键词:
酸酸酶是一种酸性酸酶.深度学习是一种深度学习.氨酸4-氧化酶是什么基质结合点是基质的结合点.

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科学领域:

  • 计算生物学是一种计算生物学.
  • 生物化学 生物化学
  • 机器学习是机器学习.

背景情况:

  • 酶工程依赖于修改酶基质结合口袋以改变催化活性.
  • 不同的基质结合点对传统的工程方法构成挑战.

研究的目的:

  • 开发一种新的3D卷积神经网络 (DUnet),用于准确预测蛋白质-连接体结合点.
  • 为了证明DUnet在指导酶工程策略中的实用性.

主要方法:

  • 开发了一个3D卷积神经网络,集成DenseNet,UNet和自我注意力.
  • 使用数据增强技术来扩大培训数据集.
  • 该模型在SC6K,COACH420和BU48数据集上得到验证,并应用于预测Klebsiella variicola酸酶 (KvAP) 和Bacillus anthracis proline 4-hydroxylase (BaP4H) 中的结合位点.

主要成果:

  • DUnet实现了高预测准确度,预测和实际结合点中心之间的距离≤4 Å.
  • 成功预测了KvAP (53.8%) 和BaP4H (56%) 的关键结合点,影响了催化.
  • 基于预测位置的虚拟和突变发生,确定了增强酶基质结合的突变.

结论:

  • 准确预测关键结合点对于成功的酶工程至关重要.
  • 杜尼特提供了一种强大的工具,用于识别关键残留物,并通过向突变发生改善酶功能.