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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
Intrinsically Disordered Proteins02:18

Intrinsically Disordered Proteins

17.8K
Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...
17.8K
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 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 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
Protein Folding01:22

Protein Folding

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Overview
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相关实验视频

Updated: Jun 24, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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蛋白质嵌入预测了无序区域中的结合残留物.

Laura R Jahn1, Céline Marquet2, Michael Heinzinger1

  • 1School of Computation, Information, and Technology (CIT), Department of Informatics, Bioinformatics and Computational Biology, TUM (Technical University of Munich), 85748, Garching/Munich, Germany.

Scientific reports
|June 12, 2024
PubMed
概括

我们开发了IDBindT5,一种使用蛋白质语言模型的机器学习模型,用于预测内在无序蛋白质中的结合区域. 这种工具为无序的蛋白质结合部位提供了快速而准确的预测.

关键词:
机器学习 机器学习它与蛋白质结合.蛋白质结合预测的预测蛋白质疾病是一种蛋白质疾病.蛋白质的功能蛋白质的功能蛋白质语言模型的模型

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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

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相关实验视频

Last Updated: Jun 24, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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科学领域:

  • 生物化学 生物化学
  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 蛋白质结合残留物对于理解生物过程和蛋白质功能至关重要.
  • 现有的方法难以准确预测内在无序蛋白质或区域 (IDPs/IDPRs) 中的结合残留物,也称为分子识别特征 (MoRFs).

研究的目的:

  • 开发一种新的机器学习模型,专门预测IDPR中的约束区域.
  • 利用蛋白质语言模型 (pLMs) 来改进蛋白质区域中结合点的预测.

主要方法:

  • 开发了IDBindT5,这是一个机器学习模型,利用了来自蛋白质语言模型ProtT5.5的嵌入式.
  • 训练和评估数据集模型,用于预测IDPR中具有约束力的区域.

主要成果:

  • 在训练数据集上,IDBindT5实现了57.2 ± 3.6% (95% CI) 的平衡精度.
  • 在相同的数据上,性能与ANCHOR2和DeepDISOBind等最先进的方法相美.
  • IDBindT5提供了显著更快的预测,使大规模的蛋白质组分析成为可能.

结论:

  • 蛋白质语言模型显示出预测受损蛋白质特征的巨大潜力.
  • IDBindT5提供了一种快速有效的方法来识别IDDPR中的约束区域.
  • 模型和手册是公开可用的,以便进一步研究.