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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
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
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
Protein Organization01:24

Protein Organization

6.0K
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....
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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基于PDFL的机器学习来预测蛋白质-连接物结合的亲和力.

Mushal Zia1, Benjamin Jones1, Hongsong Feng1

  • 1Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States.

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概括

我们介绍了一种新方法,持久定向旗拉普拉西安 (PDFL),用于分析生物分子网络中的定向相互作用. PDFL提高了蛋白质-联体结合亲和力的预测,有助于药物发现.

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科学领域:

  • 计算生物学 计算生物学
  • 网络科学 网络科学
  • 数据分析 数据分析

背景情况:

  • 定向对于理解生物系统中复杂的分子相互作用至关重要.
  • 传统的拓数据分析方法,如持久的同质性 (PH) 和持久的拉普拉斯式 (PL),往往忽略了相互作用的方向性.
  • 对分子网络的准确建模需要考虑信号转导和基因调节等过程中的不对称相互作用.

研究的目的:

  • 开发一种新的方法,持续定向的旗拉普拉西安 (PDFL),将定向性纳入拓数据分析.
  • 将PDFL应用于分析光谱图形属性,并与机器学习结合使用.
  • 评估PDFL在预测蛋白质 - 配体结合亲缘关系方面的有效性.

主要方法:

  • 使用定向旗复合体开发持久定向旗拉普拉西亚 (PDFL).
  • 将光谱图理论与机器学习算法的整合.
  • 在PDBbind数据集上验证多核PDFL模型 (v2007,v2013,v2016).

主要成果:

  • 该PDFL模型成功地将定向性纳入网络分析.
  • 与现有方法相比,PDFL在预测蛋白质 - 配体结合亲和力方面表现出卓越的准确性和可靠性.
  • 该模型只需要原始输入数据,简化了分析过程.

结论:

  • 持续定向的旗拉普拉西安 (PDFL) 是一种新且有效的工具,用于分析定向生物分子网络.
  • PDFL显著提高了蛋白质 - 配体结合亲和力的预测.
  • 在蛋白质工程,药物发现以及更广泛的科学和工程领域中,PDFL具有很大的应用潜力.