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相关概念视频

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-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
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
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

12.7K
The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
12.7K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.7K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
4.7K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

6.2K
Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
6.2K

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相关实验视频

Updated: Jun 19, 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

bindNode24:具有竞争力的结合性残留物预测,使用60%小的模型.

Kyra Erckert1,2, Franz Birkeneder1, Burkhard Rost1,3,4

  • 1TUM School of Computation, Information and Technology, Bioinformatics & Computational Biology - i12, Boltzmannstr. 3, Garching, Munich 85748, Germany.

Computational and structural biotechnology journal
|April 1, 2025
PubMed
概括
此摘要是机器生成的。

bindNode24,一种新的图形神经网络方法,可以预测小分子,金属离子和核大分子的蛋白质结合残留物. 它集成结构数据,以更少的参数改进蛋白质功能预测.

关键词:
结合性残留物的预测.结合残留物 结合残留物嵌入式 嵌入式图形神经网络是一个神经网络.机器学习 机器学习它与蛋白质结合.蛋白质语言模型的模型

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Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
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Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

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相关实验视频

Last Updated: Jun 19, 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

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

科学领域:

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

背景情况:

  • 蛋白质配体结合对于功能至关重要,但实验数据很少.
  • 现有的方法使用蛋白质语言模型嵌入来预测结合残留物.
  • 阿尔法蛋白结构数据库提供可靠的3D结构预测.

研究的目的:

  • 引入bindNode24,一种新的图形神经网络方法,用于预测蛋白质残留的结合.
  • 预测三种主要连接物类的结合:小分子,金属离子和核大分子.
  • 用最先进的方法对bindNode24进行评估.

主要方法:

  • 利用图形神经网络 (GNN) 来预测残留水平的结合.
  • 从AlphaFold2预测中整合3D结构特征.
  • 在各种蛋白质数据集上培训和评估bindNode24模型.

主要成果:

  • bindNode24准确地预测了三种配体类别的结合残留物.
  • 该方法实现了与现有方法相比较的性能.
  • 与最先进的 bindNode24 相比, bindNode24 将自由参数的数量显著减少了近 60%,与最先进的 bindNode24 相比.
  • 来自AlphaFold2的二级和三级结构特征得到了有效的整合.

结论:

  • bindNode24提供了一种高效有效的方法来预测蛋白质结合部位.
  • 整合结构信息可以提高基于GNN的蛋白质功能预测.
  • 这种方法可以通过有限的实验数据来预测蛋白质-连接体相互作用.