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相关概念视频

Protein Folding01:25

Protein Folding

8.1K
Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...
8.1K
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
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
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Multi-pass Transmembrane Proteins and β-barrels01:09

Multi-pass Transmembrane Proteins and β-barrels

5.3K
In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
α-Helix containing multi-pass transmembrane proteins
Multi-pass transmembrane proteins such as...
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Protein Organization01:13

Protein Organization

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Overview
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Protein and Protein Structure02:15

Protein and Protein Structure

79.6K
Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
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相关实验视频

Updated: Jul 11, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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改进使用结构特征的alpha-helical跨膜蛋白结构中的alphaFold预测接触.

Aman Sawhney1, Jiefu Li2, Li Liao1

  • 1Department of Computer and Information Sciences, University of Delaware, Smith Hall, 18 Amstel Avenue, Newark, DE, 19716,United States.

Research square
|November 14, 2023
PubMed
概括

利用已知的蛋白质结构显著改善了残留接触地图的预测,通过利用原子结构的特征,超越了AlphaFold2. 这提高了预测蛋白质结构和功能的准确性.

关键词:
阿尔法螺旋的螺旋阿尔法折叠的阿尔法联系人地图预测预测机器学习是机器学习.蛋白质结构 蛋白质结构蛋白质结构建模模型跨膜蛋白质是一种跨膜蛋白质.

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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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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科学领域:

  • 结构生物学是结构生物学.
  • 计算生物学是一种计算生物学.
  • 生物信息学是一种生物信息学.

背景情况:

  • 残留接触图是3D蛋白质结构的二维表示,对于结构建模和了解蛋白质功能至关重要.
  • 目前的方法主要使用基于序列的功能来预测联系地图.
  • 已知的蛋白质结构为改善未知的结构预测提供了有价值的信息,特别是当像AlphaFold2这样的近似模型可用时.

研究的目的:

  • 通过整合已知的蛋白质结构信息来提高残留接触地图预测的准确性.
  • 评估利用来自原子结构的特征来预测残留物接触的有效性.

主要方法:

  • 开发了一种新的方法,使用从残留对附近的原子结构中提取的特征.
  • 训练有素的预测模型基于从实验确定的蛋白质结构中获得的特征.
  • 应用训练的模型来预测接触,使用来自AlphaFold2预测结构的特征.

主要成果:

  • 在持有数据上达到超过91.9%的平均精度,在交叉验证上达到89.5%.
  • 与AlphaFold2的性能相比显著改善 (83%的平均精度).
  • 证实使用直接坐标,而不是衍生特征,并没有提高预测准确性.

结论:

  • 从实验确定结构的知识可以大大提高来自AlphaFold2模型的接触预测.
  • 提出的基于特征的方法显著优于现有的残留接触预测方法.
  • 这种方法提供了一种更准确的方法来使用预测模型分析蛋白质结构和功能.