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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
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

13.0K
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:
13.0K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.8K
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
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-protein Interfaces02:04

Protein-protein Interfaces

12.6K
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...
12.6K

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相关实验视频

Updated: Jul 22, 2025

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Published on: July 8, 2025

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当前的对接程序在核酸-连接接方面有多好? 一个全面的评估.

Dejun Jiang1,2, Huifeng Zhao1,2, Hongyan Du1

  • 1Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.

Journal of chemical theory and computation
|July 22, 2023
PubMed
概括

这项研究全面评估了核酸 (NA) - 连接物相互作用的分子对接程序,这对于药物发现至关重要. 植物和LeDock显示出预测结合姿势的强大潜力,优于专业的NA-ligand程序.

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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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科学领域:

  • 计算化学和结构生物学
  • 药物的发现和开发.
  • 分子建模和模拟分子模型

背景情况:

  • 核酸 (NA) - 配体相互作用对生物过程至关重要,是主要的药物标.
  • 在原子层面理解这些相互作用对于药物发现至关重要.
  • 分子对接是预测NA-体相互作用的主要计算方法,但程序性能没有很好地描述.

研究的目的:

  • 系统地评估NA-联体系统中流行的分子对接程序的性能.
  • 确定最有效的程序,用于预测NA-连接体复合体中的结合姿势和亲和关系.
  • 为在针对NA的药物发现中选择合适的计算工具提供指导.

主要方法:

  • 编制了迄今为止最大的基于结构的NA-联体结合数据集 (800个非共价复合物).
  • 评估了八个对接程序 (六个蛋白质连接体,两个NA-连接体特定) 关于结合姿势和亲和力预测.
  • 在已建立的数据集上,比较了表现最好的程序 (PLANTS,LeDock) 与较新的NA-ligand程序 (NLDock).

主要成果:

  • 植物和LeDock表现出有希望的或与专门的NA-ligand计划可比的结果.
  • 植物,rDock和LeDock在约束姿势预测方面表现出色,植物取得了最高的成功率.
  • 对大多数程序来说,绑定亲和度预测是具有挑战性的;植物显示出最好的相关性 (Rp = -0.461).

结论:

  • 植物和LeDock显示了NA-ligand对接的巨大潜力,在绑定姿势预测方面表现优于NLDock.
  • 这项研究提供了迄今为止对NA-连接体系统的分子对接程序的最全面的评估.
  • 这些发现可以指导研究人员选择最佳的计算工具,以针对NA的药物发现.