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相关概念视频

Ligand Binding Sites02:40

Ligand Binding Sites

14.9K
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...
14.9K
Ligand Binding Sites02:40

Ligand Binding Sites

8.6K
8.6K
Conserved Binding Sites01:49

Conserved Binding Sites

5.0K
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...
5.0K
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.4K
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...
14.4K
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

14.9K
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:
14.9K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

5.5K
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...
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相关实验视频

Updated: Jan 17, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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强大的预测蛋白质 - 连接体结合功率与多模式定制的门控制控制.

Bofei Xu1, Wenting Tang2, Danial Muhammad3

  • 1College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China.

Journal of chemical information and modeling
|September 25, 2025
PubMed
概括

一个新的深度学习模型,MultiMolCGC,在预测SARS-CoV-2等冠状病毒的药物效率方面表现出色. 这种先进的框架有效地捕捉了分子相互作用,超过了传统方法,并显示了抗病毒药物发现的前景.

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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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相关实验视频

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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科学领域:

  • 计算化学和药物发现
  • 在分子建模中的人工智能.
  • 开发抗病毒药物的开发.

背景情况:

  • 主蛋白酶 (Mpro) 是针对冠状病毒的抗病毒药物设计的关键目标.
  • 准确预测小分子与Mpro的结合亲和力是一个重大挑战.

研究的目的:

  • 开发和详细介绍一种新的深度学习模型,用于盲目的药物效率预测,针对SARS-CoV-2和MERS-CoV Mpro.
  • 根据传统基线评估模型的性能,并探索各种优化策略.

主要方法:

  • 使用定制的门控制框架开发一个多式多任务图注意力网络 (MultiMolCGC).
  • 整合多式分子表示和专门的多任务门架构.
  • 探索预训练策略,模型架构调整以及预测结构数据的影响.

主要成果:

  • 多MolCGC模型在一个盲目的药物强度预测挑战中取得了最佳表现.
  • 与传统机器学习基线相比,该模型表现出优异的性能.
  • 在合成对接数据上的训练在低数据条件下显著提高了性能.

结论:

  • 多MolCGC框架显示出作为一个强大而准确的深度学习工具的巨大潜力,用于预测蛋白质 - 配体结合亲和力.
  • 通过专门的多任务网关来定制知识共享是提高预测准确性的有价值的.
  • 预训练提供了一种可行的策略来提高模型性能,特别是当实验数据有限时.