Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

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
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
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
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

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Docking in the Dark: Insights into Protein-Protein and Protein-Ligand Blind Docking.

Pharmaceuticals (Basel, Switzerland)·2025
Same author

Bioisosteric and Virtual Screening Approach to Identify Natural Inhibitors of Chikunguya alphavirus nsP3.

Cell biochemistry and biophysics·2025
Same author

Medicinal Chemistry behind Capivasertib Discovery: Seventh Magic Bullet of the Fragment-based Drug Design Approved for Oncology.

Current medicinal chemistry·2025
Same author

Predicting Inhibition of CDK2 with SAnDReS: The Application of Machine Learning to Navigate the Scoring Function Space.

Current medicinal chemistry·2024
Same author

SAnDReS 2.0: Development of machine-learning models to explore the scoring function space.

Journal of computational chemistry·2024
Same author

Exploring Scoring Function Space: Developing Computational Models for Drug Discovery.

Current medicinal chemistry·2023

相关实验视频

Updated: Jun 18, 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

2.5K

机器学习与基于物理的建模相遇:一个大质量弹系统来预测蛋白质-连接体结合亲和力.

Walter Filgueira de Azevedo1

  • 1Department of Physics, Institute of Exact Sciences, Federal University of Alfenas, Av. Jovino Fernandes de Sales 2600, Bairro Santa Clara, Alfenas, MG., 37133-840, Brazil.

Current medicinal chemistry
|August 2, 2024
PubMed
概括
此摘要是机器生成的。

一个新的质量弹模型,Taba,准确地预测了对循环素依赖性激酶的蛋白质-联体结合亲和力. 这种基于物理的方法,增强了机器学习,超过了现有的对接程序药物发现.

关键词:
这是CDK.CDK.基于物理学的模型.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.质弹系统的质量弹系统

更多相关视频

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry
07:33

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

Published on: October 15, 2018

14.2K
Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

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

Published on: January 26, 2024

1.8K

相关实验视频

Last Updated: Jun 18, 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

2.5K
Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry
07:33

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

Published on: October 15, 2018

14.2K
Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

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

Published on: January 26, 2024

1.8K

科学领域:

  • 计算化学和结构生物学.
  • 药物的发现和开发.

背景情况:

  • 精确的计算评估蛋白质 - 连接体结合能量对于早期药物发现至关重要.
  • 针对性评分函数在预测结合亲和力方面表现优于通用模型.

研究的目的:

  • 审查一个简单的基于物理的质量弹模型的应用,以估计结合亲和力.
  • 为了评估这个模型的预测性能,特别是对于循环林依赖性激酶抑制剂.

主要方法:

  • 在PubMed上进行文献搜索,寻找预测绑定亲和力的质量弹模型.
  • 利用了来自蛋白质数据库的循环素依赖激酶的晶体结构.
  • 雇佣的网络服务器用于基于原子坐标的亲和度计算.

主要成果:

  • 简单的基于物理学的模型Taba评分函数有效地分析蛋白质-连接体相互作用.
  • 与已建立的基于物理的模型相比,Taba在AutoDock4和Molegro虚拟Docker中表现出卓越的性能.
  • 对27个评分函数的分析证实了Taba对循环林依赖激酶的优异预测指标.

结论:

  • 机器学习的进步和可访问的图书馆有助于开发精确的蛋白质-连接体相互作用模型.
  • 将大规模弹系统与机器学习集成,可以产生有针对性的评分功能,并增强pKi估计的预测能力.