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相关概念视频

Protein Networks02:26

Protein Networks

4.5K
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,...
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Protein Networks02:26

Protein Networks

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Protein-protein Interfaces02:04

Protein-protein Interfaces

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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...
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Protein-Protein Interfaces02:04

Protein-Protein Interfaces

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Conjugated Proteins02:50

Conjugated Proteins

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Simple proteins and protein complexes contain only amino acids. In contrast, many other proteins, called conjugated proteins, covalently bond with non-protein moieties.
Nucleoproteins are protein complexes that contain nucleic acids, categorized as deoxyribonucleoproteins (DNPs) or ribonucleoproteins (RNPs) respectively. The nucleosome is a typical example of a DNP where nuclear DNA is associated with histone proteins. The major antigen for the Covid-19 virus SARS-CoV is an RNP that is critical...
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Protein Organization01:24

Protein Organization

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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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相关实验视频

Updated: Jan 17, 2026

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro
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一个基于图形神经网络的方法,用于从多视图数据中预测SARS-CoV-2-人类蛋白相互作用.

Sumanta Ray1,2, Syed Alberuni3, Alexander Schönhuth2

  • 1Data Science Unit, The West Bengal National University of Juridical Sciences, Kolkata, West Bengal, India.

PloS one
|September 25, 2025
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概括

这项研究引入了一个深度学习模型来预测SARS-CoV-2-人类蛋白相互作用,确定了472个高可信度链接. 这促进了COVID-19治疗的药物重新定位,通过揭示潜在的候选药物,如lenalidomide.

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科学领域:

  • 计算生物学是一种计算生物学.
  • 病毒学 病毒学
  • 药物发现 药物发现

背景情况:

  • 由于COVID-19的流行,需要快速开发治疗策略.
  • 准确的分子相互作用数据对于in silico药物重定向模型至关重要.
  • 现有的SARS-CoV-2人类相互作用数据集在高可信度相互作用方面是有限的.

研究的目的:

  • 通过预测高可靠性SARS-CoV-2-人类蛋白相互作用来扩展现有资源.
  • 开发和验证基于深度学习的多视图神经网络方法,用于交互预测.
  • 为了确定COVID-19治疗的潜在药物重用候选人.

主要方法:

  • 利用基于深度学习的多视图图形神经网络方法,实现最佳的运输集成.
  • 来自蛋白质序列,基因本体学术语和物理相互作用数据的综合特征.
  • 通过全面战略验证预测,并与基线方法比较性能.

主要成果:

  • 成功预测了280个宿主蛋白和27个SARS-CoV-2蛋白之间的472个高可信度相互作用.
  • 实现了强大的预测性能,ROC-AUC得分从83.1%到85.9%不等.
  • 确定了lenalidomide和pirfenidone作为COVID-19的潜在药物重新定位候选药物.

结论:

  • 开发的多视图图神经网络框架为SARS-CoV-2-宿主蛋白相互作用提供了准确和全面的预测.
  • 这些发现为加快对抗COVID-19的药物重定向努力提供了宝贵的资源.
  • 该研究强调了整合多种数据源的潜力,以改善分子相互作用预测.