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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
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
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

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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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AQDnet:深度神经网络用于蛋白质 - 连接体对接模拟.

Koji Shiota1, Akira Suma1, Hiroyuki Ogawa1

  • 1Innovation to Implementation Laboratories, Central Pharmaceutical Research Institute, Japan Tobacco Inc., Takatsuki, Osaka 569-1125, Japan.

ACS omega
|July 10, 2023
PubMed
概括

我们开发了AI QM对接网 (AQDnet) 用于使用量子计算和以原子为中心的对称函数来预测蛋白质 - 连接体结合亲和力. 我们的新系统在对接功率方面取得了92.6%的成功率,超过了所有其他模型.

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科学领域:

  • 计算化学是一种计算化学.
  • 结构生物学是结构生物学.
  • 药物发现 药物发现

背景情况:

  • 准确预测蛋白质 - 配体结合亲和力对于药物发现至关重要.
  • 现有的方法在捕捉蛋白质-连接体复合体内的复杂相互作用方面面临挑战.
  • 量子力学计算提供了高精度,但对于大型数据集而言,计算成本昂贵.

研究的目的:

  • 开发一个创新的系统,AI QM Docking Net (AQDnet),用于预测蛋白质 - 连接体结合亲和力.
  • 通过生成多样化的连接体配置和通过量子计算计算结合能量的计算来增强训练数据集.
  • 纳入原子中心对称函数 (ACSF) 以改善蛋白质 - 连接体相互作用的预测.

主要方法:

  • 为每个蛋白质-连接体复合体生成数千种不同的连接体配置.
  • 使用量子计算确定每个配置的结合能.
  • 使用ACSF培训在蛋白质-连接体量子能量格局 (P-L QEL) 上的神经网络的开发.

主要成果:

  • 在CASF-2016对接功率基准中取得了92.6%的顶级成功率.
  • 在CASF-2016评估中,AQDnet的表现优于之前评估的所有模型.
  • 证明了ACSF在预测蛋白质 - 配体相互作用方面的有效性.

结论:

  • AQDnet在预测蛋白质 - 连接体结合亲和力方面取得了重大进展.
  • 该系统对数据集扩展和ACSF集成的新方法导致了卓越的对接性能.
  • 这种模式对加速药物发现和开发过程具有很大的前景.