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 Folding01:25

Protein Folding

7.9K
Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...
7.9K
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 Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.1K
Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
2.1K
Protein Organization01:24

Protein Organization

6.3K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
6.3K
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 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

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 Hybrid Physics-Deep Learning Framework for Combinatorial De Novo Design of Small-Molecule Binding Proteins.

bioRxiv : the preprint server for biology·2026
Same author

Structural ontogeny of protein-protein interactions.

Science (New York, N.Y.)·2026
Same author

A combinatorial mutational map of active non-native protein kinases by deep learning guided sequence design.

bioRxiv : the preprint server for biology·2025
Same author

The biophysical requirements that govern the efficient endosomal escape of designed mini-proteins.

Nature chemistry·2025
Same author

An improved model for prediction of de novo designed proteins with diverse geometries.

bioRxiv : the preprint server for biology·2025
Same author

Deep learning-guided design of dynamic proteins.

Science (New York, N.Y.)·2025

相关实验视频

Updated: Jun 18, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.0K

深度学习指导动态蛋白质的设计.

Amy B Guo1,2, Deniz Akpinaroglu1,2, Mark J S Kelly3

  • 1The UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, CA 94143, USA.

bioRxiv : the preprint server for biology
|July 29, 2024
PubMed
概括

科学家们开发了一种新的深度学习方法来设计动态蛋白质结构,首次能够精确控制蛋白质运动和信号行为.

更多相关视频

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
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.3K

相关实验视频

Last Updated: Jun 18, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.0K
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
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.3K

科学领域:

  • * 计算生物学和结构生物学.
  • * 蛋白质工程和设计.
  • * 分子动力学和生物物理学.

背景情况:

  • * 深度学习已经推进了静态蛋白质结构设计.
  • * 交换机样信号蛋白中受控的构造动力学仍然对新的设计具有挑战性.

研究的目的:

  • * 开发一种以深度学习为指导的通用方法,用于动态蛋白质构造变化的新设计.
  • * 在设计类似开关的蛋白质机制时实现原子级精度.
  • * 创建可调和可控制的蛋白质信号行为.

主要方法:

  • * 采用深度学习指导的策略来设计新型蛋白质.
  • * 解决了四个蛋白质结构以验证设计的结构.
  • *采用了微秒级分子动力学模拟.
  • * 通过连接体和突变研究了形状景观的调制.
  • * 进行基于物理的模拟来分析残留物相互作用和预测突变.

主要成果:

  • *成功设计和验证了蛋白质的动态形状变化.
  • * 在设计状态之间证明了微秒过渡.
  • * 显示,构造性景观可以通过orthosteric连接体和allosteric突变来调节.
  • * 基于物理的模拟证实了与深度学习预测和实验数据的一致性.
  • *确定了依赖状态的残留物相互作用网络和预测的有效突变.

结论:

  • * 一种通用的深度学习方法可以重新设计动态蛋白质构造变化.
  • *设计的蛋白质表现出可调和可控制的信号行为.
  • * 这一框架为设计新型蛋白质功能和生物机制开辟了新的可能性.