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相关概念视频

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 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-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

161
Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
161
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 Networks02:26

Protein Networks

3.9K
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,...
3.9K
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

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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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机器学习方法在蛋白质对蛋白质对接中

Ilona Michalik1, Kamil J Kuder2

  • 1Department of Technology and Biotechnology of Drugs, Faculty of Pharmacy, Jagiellonian University Medical College, Kraków, Poland.

Methods in molecular biology (Clifton, N.J.)
|July 10, 2024
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概括

人工智能 (AI) 正在彻底改变生命科学,特别是在研究蛋白质与蛋白质相互作用方面. 本章介绍了用于分析这些相互作用的AI方法,尽管存在数据质量和预测蛋白质变化等挑战.

关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.机器学习是机器学习.蛋白质蛋白质是一种蛋白质.蛋白质蛋白质对接蛋白质蛋白质相互作用结构生物学是结构生物学.

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科学领域:

  • 生命科学 生命科学
  • 计算生物学 计算生物学
  • 人工智能的人工智能

背景情况:

  • 在生命科学中,关于人工智能 (AI) 的出版物越来越多.
  • 人工智能为了解细胞过程和药物发现提供了巨大的潜力.
  • 蛋白质与蛋白质的相互作用对生物系统至关重要,但在计算上具有挑战性.

研究的目的:

  • 为研究蛋白质-蛋白质相互作用提供AI方法的介绍.
  • 描述目前用于人工智能驱动蛋白相互作用分析的算法和程序.
  • 突出现场的挑战,例如数据量和预测结构变化.

主要方法:

  • 对各种适用于蛋白质-蛋白质相互作用研究的人工智能技术的审查.
  • 描述最先进的算法和软件工具.
  • 专注于分析生物系统的计算方法.

主要成果:

  • 人工智能方法在生命科学中越来越多地用于复杂的生物学问题.
  • 蛋白质相互作用分析的计算工具取得了重大进展.
  • 预计将持续开发新的AI算法.

结论:

  • 人工智能是推动蛋白质与蛋白质相互作用研究的强大工具.
  • 尽管面临挑战,但人工智能为理解生物系统和药物发现提供了有前途的解决方案.
  • 该领域正在迅速发展,新型人工智能技术的不断出现.