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相关概念视频

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

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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...
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The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

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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:
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Ligand Binding and Linkage00:49

Ligand Binding and Linkage

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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...
4.8K
The Two-State Receptor Model01:29

The Two-State Receptor Model

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The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
The binding affinity of a drug determines its interaction with...
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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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基于药理分子的机器学习模型来预测E3联酶结合物的联选择性.

Reagon Karki1,2, Yojana Gadiya1,2,3, Philip Gribbon1,2

  • 1Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany.

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这项研究引入了一种快速,廉价的机器学习模型,使用药指纹来预测E3酶结合剂,有助于药物发现和开发.

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科学领域:

  • 生物化学 生物化学
  • 计算化学计算化学
  • 药物发现 药物发现 药物发现

背景情况:

  • E3酶是蛋白质降解中的关键酶,调节许多细胞过程.
  • 药分析有助于预测蛋白标的连接体结合选择性.
  • 准确预测连接体结合亲和力仍然是药物设计中的一个挑战.

研究的目的:

  • 开发一种快速且具有成本效益的方法来预测E3结合酶结合剂.
  • 为了利用药指纹和机器学习来预测E3酶结合.
  • 为了实现针对E3结合酶的小分子的合理设计.

主要方法:

  • 采用了ErG药剂师指纹采集方案.
  • 开发了一个多类机器学习分类模型.
  • 应用该模型来预测分子的E3酶结合剂概率.

主要成果:

  • 该模型准确地将已知的E3结合酶结合剂分配给它们各自的标.
  • 它预测了分子在各种E3结合酶的结合概率.
  • 在像Asinex.com这样的商业复合库上展示了实际应用.

结论:

  • 开发的方法提供了一个有价值的工具,用于过和设计专注的图书馆,用于E3酶选.
  • 这种方法促进了新型E3结合酶结合剂的合理设计.
  • 该计算模型为针对E3连接酶的药物发现工作提供了一个有效的策略.