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相关概念视频

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

12.9K
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...
12.9K
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 Networks02:26

Protein Networks

4.0K
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,...
4.0K
Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

196
Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
196
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

12.9K
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:
12.9K

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相关实验视频

Updated: Jul 7, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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APIPred:一种基于XGBoost的方法,用于预测Aptamer-蛋白相互作用.

Zheng Fang1,2,3, Zhongqi Wu1,2,4, Xinbo Wu5

  • 1Holonyak Micro and Nanotechnology Lab (HMNTL), University of Illinois at Urbana-Champaign, Champaign-Urbana 61801, United States.

Journal of chemical information and modeling
|December 21, 2023
PubMed
概括

这项研究引入了一种计算方法来预测胺蛋白相互作用,加速发现生物传感和疾病治疗的胺蛋白. 新型号实现了高精度,改进了现有技术.

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In Vitro Selection of Aptamers to Differentiate Infectious from Non-Infectious Viruses
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Mapping the Binding Site of an Aptamer on ATP Using MicroScale Thermophoresis
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相关实验视频

Last Updated: Jul 7, 2025

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In Vitro Selection of Aptamers to Differentiate Infectious from Non-Infectious Viruses
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科学领域:

  • 生物技术是生物技术.
  • 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:

  • 单链DNA或RNA寡核酸的aptamers为目标结合提供了高特异性,并且在生物传感和疾病治疗中至关重要.
  • 传统的体生成过程,即SELEX (指数式丰富联体的系统演化),是漫长且资源密集的.

研究的目的:

  • 开发和验证用于预测体-蛋白相互作用的计算模型,从而加速体选择.
  • 为了提高效率,并减少用于治疗和诊断应用的功能性aptamer的识别所需的时间.

主要方法:

  • 使用in silico和计算工具来分析蛋白质和aptamer对数据.
  • 开发和评估了多种机器学习模型,用于预测体蛋白相互作用.
  • 使用分子对接和表面等离子体共振 (SPR) 结合试验验验证的模型预测.

主要成果:

  • 通过一个开发的机器学习模型,实现了高预测准确度 (96.5%) 和精度 (97%),超过了以前的基准.
  • 通过通过分子对接和SPR试验的实验验证,证明了APIPred算法的稳定性.
  • 该模型有效地预测了胺蛋白结合的选择性.

结论:

  • 开发的计算方法显著增强了对胺体与蛋白质相互作用的预测.
  • 这种高通量查模型提供了一种快速的方法来识别针对癌症和病毒流行病等疾病的aptamer候选者.
  • APIPred算法为推进基于aptamer的诊断和治疗提供了一个有价值的工具.