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相关概念视频

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
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
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

12.9K
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:
12.9K
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 Networks02:26

Protein Networks

4.0K
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,...
4.0K

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相关实验视频

Updated: Jul 4, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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PLAS-20k:来自机器学习应用程序的MD模拟的蛋白质 - 连接物亲缘关系的扩展数据集.

Divya B Korlepara1,2, Vasavi C S1,3, Rakesh Srivastava4

  • 1IHub-Data, International Institute of Information Technology, Hyderabad, 500032, India.

Scientific data
|February 9, 2024
PubMed
概括

一个新的大规模数据集,PLAS-20k,捕获动态蛋白质-连接体相互作用,以改善药物发现中的结合亲和力预测. 这一数据集增强了机器学习模型的性能,超过了传统的对接分数.

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科学领域:

  • 计算化学是一种计算化学.
  • 结构生物学是结构生物学.
  • 机器学习在药物发现中的作用

背景情况:

  • 准确预测蛋白质 - 连接体结合亲和关系对于有效的药物发现至关重要.
  • 目前的机器学习模型由于缺乏现有数据集中的动态交互数据而陷入困境.

研究的目的:

  • 开发PLAS-20k数据集,其中包括蛋白质-连接体相互作用的动态特征.
  • 为开发用于绑定亲和度预测的先进机器学习模型提供一个基准.

主要方法:

  • 生成了PLAS-20k数据集,其中包含97,500个模拟,用于19,500个蛋白质-连接体复合体.
  • 使用PLAS-20k数据集重新训练了OnionNet模型.
  • 对实验值和对接分数进行模型性能评估.

主要成果:

  • PLAS-20k数据集显示了与实验性结合亲和关系的良好相关性.
  • 该数据集改善了对遵循利宾斯基规则的连接体和各种复杂结构的预测.
  • 数据集有助于比对接更有效地分类强 binders 和弱 binders.

结论:

  • PLAS-20k数据集是开发药物发现下一代机器学习模型的宝贵资源.
  • 基于大规模分子动力学 (MD) 的数据集可以加速药物发现管道.
  • 整合动态特征显著提高了结合亲和力预测的准确性.