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 Organization01:24

Protein Organization

9.0K
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....
9.0K
Protein Organization01:13

Protein Organization

155.5K
Overview
155.5K
Conserved Binding Sites01:49

Conserved Binding Sites

5.0K
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...
5.0K
Ligand Binding Sites02:40

Ligand Binding Sites

14.8K
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...
14.8K
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.4K
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...
14.4K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

4.4K
4.4K

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

TransG4: an interpretable deep-learning approach for sequence-based G-quadruplex prediction.

Physical chemistry chemical physics : PCCP·2026
Same author

InChINet: a self-supervised molecular representation learning framework leveraging SMILES and InChI.

Physical chemistry chemical physics : PCCP·2026
Same author

Virtual Bonding Enhanced Graph Self-Supervised Learning for Molecular Property Prediction.

Journal of computational chemistry·2025
Same author

MutualDTA: An Interpretable Drug-Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention.

Journal of chemical information and modeling·2025
Same author

Kinetic Ensemble of Tau Protein through the Markov State Model and Deep Learning Analysis.

Journal of chemical theory and computation·2024
Same author

Quantum Chemical Calculations with Machine Learning for Multipolar Electrostatics Prediction in RNA: An Application to Pentose.

Journal of chemical information and modeling·2022

相关实验视频

Updated: Jan 8, 2026

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

69.6K

LMProtein:一种基于蛋白质语言模型的框架,用于蛋白质结构性质预测.

Yongna Yuan1, Hui Luo1, Yaojie Tian1

  • 1School of Information Science & Engineering, Lanzhou University, South Tianshui Road, Lanzhou 730000, Gansu, China. yuanyn@lzu.edu.cn.

Physical chemistry chemical physics : PCCP
|December 23, 2025
PubMed
概括

LMProtein只使用初级序列准确地预测蛋白质的结构性质,绕过计算密集的进化数据. 这种快速的框架增强了蛋白质工程和药物发现,通过对缺乏同类蛋白质的蛋白质进行预测.

科学领域:

  • 计算生物学是一种计算生物学.
  • 结构生物学中的机器学习

背景情况:

  • 机器学习和深度语言模型推进了蛋白质结构预测.
  • 目前的方法通常依赖于多重序列对齐 (MSAs),这在计算上是密集的,对于没有同类蛋白质的蛋白质是失败的.

研究的目的:

  • 开发一个快速而准确的框架 (LMProtein) 用于仅使用主要序列来预测蛋白质的结构性质.
  • 为了克服MSA依赖方法的局限性.

主要方法:

  • LMProtein结合了未经监督的预训练语言模型ESM-2与卷积神经网络 (CNN),长期短期记忆网络 (LSTM) 和多层感知器 (MLP).
  • 该框架预测了二次结构,二面角,光和稳定性景观.

主要成果:

  • LMProtein的表现优于最近的基于MSA和单序模型.
  • 在八个状态的二次结构 (SS8) 预测中获得了~74%的准确性.
  • 获得的二面角的平均绝对误差为19° (Phi) 和29° (Psi).
  • 斯皮尔曼的相关系数为光的0.69和稳定性的0.79.

结论:

  • LMProtein为预测蛋白质结构性质提供了一个计算效率高,准确的替代方案.

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

2.5K
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

888

相关实验视频

Last Updated: Jan 8, 2026

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

69.6K
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

2.5K
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

888
  • 该框架具有加速蛋白质工程和药物标识的巨大潜力,特别是对于缺乏同源序列的蛋白质.