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

Protein-protein Interfaces02:04

Protein-protein Interfaces

13.2K
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...
13.2K
Conserved Binding Sites01:49

Conserved Binding Sites

4.3K
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...
4.3K
Noncovalent Attractions in Biomolecules02:35

Noncovalent Attractions in Biomolecules

54.5K
Noncovalent attractions are associations within and between molecules that influence the shape and structural stability of complexes. These interactions differ from covalent bonding in that they do not involve sharing of electrons.
Four types of noncovalent interactions are hydrogen bonds, van der Waals forces, ionic bonds, and hydrophobic interactions.
Hydrogen bonding results from the electrostatic attraction of a hydrogen atom covalently bonded to a strong-electronegative atom like oxygen,...
54.5K
Ligand Binding Sites02:40

Ligand Binding Sites

13.1K
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...
13.1K
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

13.4K
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:
13.4K
Protein Networks02:26

Protein Networks

4.1K
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,...
4.1K

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

Steric Control of Cooperative Anion Transport Mediated by β- and δ‑Hexachlorocyclohexane Multivalent Carriers.

JACS Au·2026
Same author

ARNy plotter: A comprehensive web server for RNA ensemble structural analysis and visualization.

PLoS computational biology·2026
Same author

Determining the Optimal Structural Resolution of Proteins through an Information-Theoretic Analysis of Their Conformational Ensemble.

Journal of chemical theory and computation·2026
Same author

Improving the Reliability of Molecular String Representations for Generative Chemistry.

Journal of chemical information and modeling·2025
Same author

Dynamic Regulation of Proton and Water Transport through an Acylhydrazone-Based Photoresponsive Channel.

Journal of the American Chemical Society·2025
Same author

State-Dependent Dynamic Communication Networks in a Pentameric Ligand-Gated Ion Channel.

The journal of physical chemistry. B·2025

相关实验视频

Updated: Sep 9, 2025

Novel RNA-Binding Proteins Isolation by the RaPID Methodology
11:19

Novel RNA-Binding Proteins Isolation by the RaPID Methodology

Published on: September 30, 2016

9.1K

统计分子相互作用场:用于表征RNA和蛋白质结合口袋的快速和信息化工具

Diego Barquero Morera1, Giovanni Mattiotti1, Alexandar Kocev1

  • 1Laboratoire Biologie Functionnelle et Adaptative, Université Paris Cité, Inserm ERL U1133, 35 Rue Hélène Brion, Paris 75013, France.

Journal of chemical theory and computation
|September 1, 2025
PubMed
概括
此摘要是机器生成的。

研究人员开发了统计分子相互作用场 (SMIF) 来分析药物设计中的宏分子相互作用. 这种新方法提供了一种更快,更容易理解的方法,即对RNA和其他宏分子的结合.

更多相关视频

Measuring Biomolecular DSC Profiles with Thermolabile Ligands to Rapidly Characterize Folding and Binding Interactions
09:15

Measuring Biomolecular DSC Profiles with Thermolabile Ligands to Rapidly Characterize Folding and Binding Interactions

Published on: November 21, 2017

8.4K
An Assay for Quantifying Protein-RNA Binding in Bacteria
07:02

An Assay for Quantifying Protein-RNA Binding in Bacteria

Published on: June 12, 2019

6.7K

相关实验视频

Last Updated: Sep 9, 2025

Novel RNA-Binding Proteins Isolation by the RaPID Methodology
11:19

Novel RNA-Binding Proteins Isolation by the RaPID Methodology

Published on: September 30, 2016

9.1K
Measuring Biomolecular DSC Profiles with Thermolabile Ligands to Rapidly Characterize Folding and Binding Interactions
09:15

Measuring Biomolecular DSC Profiles with Thermolabile Ligands to Rapidly Characterize Folding and Binding Interactions

Published on: November 21, 2017

8.4K
An Assay for Quantifying Protein-RNA Binding in Bacteria
07:02

An Assay for Quantifying Protein-RNA Binding in Bacteria

Published on: June 12, 2019

6.7K

科学领域:

  • 计算化学
  • 结构生物学
  • 药物发现

背景情况:

  • 基于结构的药物设计需要了解宏分子-连接体相互作用.
  • 虽然RNA是药物设计的新兴目标, 但计算工具有限.
  • 现有的分子相互作用场 (MIF) 方法是准确的,但特定于合作伙伴.

研究的目的:

  • 开发一种简化,广泛适用的方法来表征宏分子结合点.
  • 创建统计分子相互作用场 (SMIF) 来分析与RNA和其他宏分子的相互作用.
  • 在药物设计中实现分子相互作用的快速大规模分析.

主要方法:

  • 开发SMIF,使用以粗粒度模型为灵感的功能形式.
  • 使用 PDB 结构和常见相互作用的统计分析 (H 键,堆积,疏水) 的参数化 SMIF.
  • 在大型系统上实现了优化的代码.

主要成果:

  • SMIF提供了与药理模型相一致的信息交互概况.
  • 计算速度很快,可以分析大数据集和整个宏分子.
  • 在复杂环境 (膜,多重分子复合体) 中分析相互作用的能力.

结论:

  • SMIF提供了一种有价值的,简化的方法来理解宏分子-连接体相互作用.
  • 该方法是有效的,适用于RNA和其他大型生物分子.
  • 促进基于结构的药物设计和理解生物系统的分析.