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Ligand Binding Sites02:40

Ligand Binding Sites

12.9K
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...
12.9K
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-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

210
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...
210
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 10, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

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

Published on: February 23, 2024

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从蛋白质到体:解码深度学习方法用于绑定亲和力预测.

Rohan Gorantla1,2, Alžbeta Kubincová3, Andrea Y Weiße1,4

  • 1School of Informatics, University of Edinburgh, Edinburgh, EH8 9AB, U.K.

Journal of chemical information and modeling
|November 20, 2023
PubMed
概括
此摘要是机器生成的。

预测蛋白质-连接体结合亲和力的深度学习模型严重依赖连接体数据,而不是蛋白质编码. 提高通用性需要专注于模型如何解释药物发现的配体信息.

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

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相关实验视频

Last Updated: Jul 10, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

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

Published on: February 23, 2024

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

209

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.
  • 药物发现 药物发现

背景情况:

  • 准确的in silico预测蛋白质 - 配体结合亲和力对于早期药物发现至关重要.
  • 当前的深度学习方法与传统技术 (如千兆对接) 相比,缺乏通用性.
  • 从蛋白质和配体数据中理解模型学习是提高概括性的关键.

研究的目的:

  • 系统地研究基于序列的深度学习框架,用于预测绑定亲和关系.
  • 评估各种蛋白质和配体编码对预测准确性的影响.
  • 评估不同蛋白质接触生成方法和连接体扰动的影响.

主要方法:

  • 使用基于卷积神经网络 (CNN) 和图形神经网络 (GNN) 的编码来编码蛋白质和连接体.
  • 使用由AlphaFold2,Pconsc4和ESM-1b生成的蛋白质接触地图,以及随机对照.
  • 通过随机化节点和边缘属性来测试连接体编码,以评估数据依赖性.

主要成果:

  • 蛋白质编码对KIBA数据集的多个指标 (一致性指数,皮尔森的R,斯皮尔曼的排名,RMSE) 的结合亲和力预测没有显著影响.
  • 观察到对联体编码的显著差异,特别是在使用随机联体或随机联体节点属性时.
  • 通过不同方式组合蛋白质和配体编码并没有产生显著的性能改善.

结论:

  • 用于结合亲和力预测的深度学习模型显示,对连接体数据特征的依赖性比对蛋白质编码的依赖性更强.
  • 选择蛋白质接触生成方法对预测性能的影响有限.
  • 进一步的研究应侧重于优化连接体表征和特征工程,以提高药物发现中的模型通用性.