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

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-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
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
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-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 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

A protein surface-aware multimodal framework for residue-level metal-binding site recognition.

Cell reports methods·2026
Same author

Integrated dynamic control and enzyme co-localization strategies enable high-efficiency stilbenoid biosynthesis.

Bioresource technology·2026
Same author

TransMarker: Unveiling dynamic network biomarkers in cancer progression through cross-state graph alignment and optimal transport.

PLoS computational biology·2025
Same author

LogicSR: prior-guided symbolic regression for gene regulatory network inference from single-cell transcriptomics data.

Briefings in bioinformatics·2025
Same author

MOFNet: a deep learning framework for multi-omics data fusion in cancer subtype classification.

Molecular omics·2025
Same author

soFusion: facilitating tissue structure identification via spatial multi-omics data fusion.

Briefings in bioinformatics·2025
Same journal

Correction to "Nanoparticles (NPs)-Meditated LncRNA AFAP1-AS1 Silencing to Block Wnt/β-Catenin Signaling Pathway for Synergistic Reversal of Radioresistance and Effective Cancer Radiotherapy".

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same journal

Femtosecond-Laser Nanocavitation Regenerates SERS-Active Plasmonic Nanogaps for Longitudinal Molecular Sensing at Biointerfaces.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same journal

Correction to "Bioinspired Polyacrylic Acid-Based Dressing: Wet Adhesive, Self-Healing, and Multi-Biofunctional Coacervate Hydrogel Accelerates Wound Healing".

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same journal

Non-Line-of-Sight Passive Ammonia Sensor Loaded With MXene/In<sub>2</sub>O<sub>3</sub> Composites for Agricultural Products Quality Deterioration Detection.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same journal

Cerium Nanoparticle-Mediated Inhibition of the NSUN2/m<sup>5</sup>C Axis Suppresses Synovial Aggression in Rheumatoid Arthritis.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same journal

Biomimetic Nanoplatform for Dual Target Nano-Metabolic Therapy in Diabetes-Associated Biofilm Infections.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
查看所有相关文章

相关实验视频

Updated: Jun 21, 2025

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

3.5K

MuToN通过几何深度学习量化蛋白质突变的绑定亲和力变化.

Pengpai Li1, Zhi-Ping Liu1

  • 1Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, Shandong, 250061, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|July 12, 2024
PubMed
概括
此摘要是机器生成的。

预测突变如何改变蛋白质结合亲和力对细胞生物学至关重要. 一种新的几何深度学习方法MuToN准确量化了这些亲和力变化,优于现有的方法和分析病毒变异.

关键词:
结合性亲和力是一种结合性亲和力.几何深度学习的几何深度学习突变是一种突变.

更多相关视频

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
06:38

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Published on: February 7, 2019

8.7K
Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions
10:44

Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions

Published on: October 21, 2016

30.6K

相关实验视频

Last Updated: Jun 21, 2025

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

3.5K
High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
06:38

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Published on: February 7, 2019

8.7K
Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions
10:44

Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions

Published on: October 21, 2016

30.6K

科学领域:

  • 计算生物学是一种计算生物学.
  • 结构生物学是结构生物学.
  • 生物物理学的生物物理.

背景情况:

  • 了解因突变而导致的蛋白质-蛋白质结合亲和力变化对于细胞过程至关重要.
  • 由于复杂的生物机制,对这些亲和力变化的准确计算预测仍然是一个重大挑战.

研究的目的:

  • 引入MuToN,一种新的几何深度学习框架,用于量化残留突变对蛋白质结合亲缘关系的变化.
  • 开发一种机制意识的方法,以捕捉接口变化和全效应.

主要方法:

  • 在深度学习框架内利用几何注意力网络.
  • 设计了一种分析突变复合体蛋白结合界面变化的方法.
  • 纳入对氨基酸的全osteric 作用的评估.

主要成果:

  • 与现有的计算方法相比,MuToN表现出更高的性能.
  • 该框架准确地预测了与ACE2复合体相互作用的SARS-CoV-2变种的结合亲和力变化.
  • 实验结果验证了MuToN的有效性和灵活性.

结论:

  • MuToN提供了一种强大而准确的方法来预测突变诱导的结合亲和力变化.
  • 该方法的机制意识设计增强了其预测能力.
  • MuToN对病毒变异的应用突显了其在理解传染病方面的实际意义.