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相关概念视频

Conserved Binding Sites01:49

Conserved Binding Sites

4.1K
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...
4.1K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.4K
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...
12.4K
Intrinsically Disordered Proteins02:18

Intrinsically Disordered Proteins

17.6K
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...
17.6K
Ligand Binding Sites02:40

Ligand Binding Sites

12.6K
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...
12.6K
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 Organization01:24

Protein Organization

6.1K
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....
6.1K

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相关实验视频

Updated: May 20, 2025

Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins
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Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins

Published on: September 23, 2021

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AIUPred - 绑定:能源嵌入来识别混乱的绑定区域

Gábor Erdős1, Norbert Deutsch1, Zsuzsanna Dosztányi1

  • 1Department of Biochemistry, Eötvös Loránd University, Pázmány Péter stny 1/c, Budapest H-1117, Hungary.

Journal of molecular biology
|March 26, 2025
PubMed
概括

在内在无序区域 (IDR) 中预测功能位点具有挑战性. AIUPred-binding使用能量嵌入和病原性得分来准确识别这些关键的无序结合区域.

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:

  • 内在无序区域 (IDR) 对于细胞功能至关重要,通过无序结合区域调解相互作用.
  • IDRs的实验性表征是困难的,需要高效的计算预测工具.
  • 在IDR中预测功能站点受到数据集限制和现有方法的阻碍.

研究的目的:

  • 开发和介绍AIUPred-binding,这是一种用于预测内在无序区域内功能站点的新型计算工具.
  • 通过利用先进的计算方法,提高识别无序绑定区域的准确性.

主要方法:

  • 利用结构能量的高维数学表示,称为"能量嵌入".
  • 综合致病性得分来自AlphaMissense.
  • 采用转移学习方法来提高预测准确度.
  • 开发AIUP预约作为一种新的预测工具.

主要成果:

  • AIUP预约显示,在IDR中识别功能部位的准确性有所提高.
  • 该工具有效地识别了混乱区域内的微妙特征.
  • 解决了手动策划数据集固有的偏见和挑战.
  • AIUPred-binding已集成到AIUPred网络框架中.
关键词:
疾病绑定预测的预测.能源嵌入式 能源嵌入式功能障碍是一种功能障碍.功能障碍预测功能障碍的预测蛋白质疾病是一种蛋白质疾病.

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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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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

Published on: January 26, 2024

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相关实验视频

Last Updated: May 20, 2025

Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins
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Paramagnetic Relaxation Enhancement for Detecting and Characterizing Self-Associations of Intrinsically Disordered Proteins

Published on: September 23, 2021

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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

Published on: July 14, 2015

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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

Published on: January 26, 2024

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结论:

  • AIUPred-binding为研究IDR的功能角色提供了一个多功能和高效的资源.
  • 该工具克服了先前用于预测无序绑定区域的方法的局限性.
  • AIUPred-binding是免费访问的,促进了该领域更广泛的研究.