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 Folding01:22

Protein Folding

117.7K
Overview
117.7K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

10.8K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
10.8K
Protein Families02:47

Protein Families

15.3K
Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
15.3K
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
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-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

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

On the state of protein function prediction: a report on the fourth CAFA challenge.

bioRxiv : the preprint server for biology·2026
Same author

HiC4D-SPOT: a spatiotemporal outlier detection tool for Hi-C data.

Briefings in bioinformatics·2025
Same author

scHiGex: predicting single-cell gene expression based on single-cell Hi-C data.

NAR genomics and bioinformatics·2025
Same author

C2c: Predicting Micro-C from Hi-C.

Genes·2024
Same author

EGG: Accuracy Estimation of Individual Multimeric Protein Models Using Deep Energy-Based Models and Graph Neural Networks.

International journal of molecular sciences·2024
Same author

Learning Micro-C from Hi-C with diffusion models.

PLoS computational biology·2024
Same journal

An epigenetic clock for chronological age estimation in East Asian populations.

NAR genomics and bioinformatics·2026
Same journal

The role of ATF4 in neurons under mitochondrial stress.

NAR genomics and bioinformatics·2026
Same journal

Distinct repeat architecture landscapes in the proteomes of protozoan parasites.

NAR genomics and bioinformatics·2026
Same journal

Long non-coding RNA triplex-dependent regulation of melanoma gene networks.

NAR genomics and bioinformatics·2026
Same journal

Challenges in predicting chromatin accessibility differences between species.

NAR genomics and bioinformatics·2026
Same journal

Power-law penalties correct distance bias in single-cell co-accessibility and deep-learning chromatin interaction predictions.

NAR genomics and bioinformatics·2026
查看所有相关文章

相关实验视频

Updated: Jun 17, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.6K

潘达-3D:基于AlphaFold模型的蛋白质功能预测.

Chenguang Zhao1, Tong Liu2, Zheng Wang2

  • 1Computer and Information Sciences Department, St. Ambrose University, 518 W Locust St, Davenport, IA 52803, USA.

NAR genomics and bioinformatics
|August 7, 2024
PubMed
概括
此摘要是机器生成的。

潘达-3D是一种新的深度学习工具,使用AlphaFold结构预测蛋白质功能. 它的性能优于现有的方法,使得AlphaFold DB中数以百万计的蛋白质能够准确地进行注释.

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
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

相关实验视频

Last Updated: Jun 17, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.6K
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
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

科学领域:

  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.
  • 结构生物学 结构生物学

背景情况:

  • 蛋白质功能预测传统上依赖于氨基酸序列.
  • 有限的实验结构和预测的结构质量差,阻碍了基于结构的方法.
  • 阿尔法折叠蛋白质结构数据库 (AlphaFold DB) 提供了一个快速增长的预测蛋白质三级结构的资源.

研究的目的:

  • 开发一个深度学习工具,PANDA-3D,用于从AlphaFold预测的蛋白质结构中预测基因本体学 (GO) 术语.
  • 为了利用不断扩展的AlphaFold DB进行增强的蛋白质功能注释.
  • 创建一个专门训练在AlphaFold模型上的工具.

主要方法:

  • 开发了一个先进的深度学习架构,结合了几何向量感知图神经网络和变压器解码器层.
  • 从一个大型语言模型中使用AlphaFold预测的结构和氨基酸序列嵌入来训练模型.
  • 实施了多标签分类方法用于GO期预测.

主要成果:

  • 潘达-3D显著优于在实验结构上训练的最先进的深度学习方法.
  • 在使用氨基酸序列的其他主要基于语言模型的方法中,PANDA-3D实现了与其他领先的使用氨基酸序列的方法相比的或更高的性能.
  • 该工具是为AlphaFold模型量身定制的,方便对庞大的AlphaFold DB进行注释.

结论:

  • PANDA-3D使用AlphaFold结构提供了准确的蛋白质功能注释.
  • 该工具对于对AlphaFold DB中大量且不断增长的蛋白质进行注释非常有价值.
  • 可以通过Web服务器和GitHub仓库访问PANDA-3D.