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Protein Organization01:24

Protein Organization

6.5K
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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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...
79.6K
Protein Families02:47

Protein Families

15.3K
Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
15.3K
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
Protein Folding01:22

Protein Folding

118.2K
Overview
118.2K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
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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相关实验视频

Updated: Jul 6, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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引导发现蛋白质序列结构功能建模的指导性发现.

Azam Hussain1, Charles L Brooks Iii2

  • 1Department of Macromolecular Science and Engineering Program, University of Michigan, Ann Arbor, MI 48109-1055, United States.

Bioinformatics (Oxford, England)
|January 9, 2024
PubMed
概括
此摘要是机器生成的。

我们开发了一个计算管道来预测蛋白质功能,加速蛋白质工程. 这种in silico方法使用AlphaFold2和对接来指导新型催化剂的设计,以改进酶选择性和反应性.

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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

Last Updated: Jul 6, 2025

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16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

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科学领域:

  • 生物化学和分子生物学
  • 计算生物学 计算生物学
  • 蛋白质工程是指蛋白质工程.

背景情况:

  • 蛋白质工程对于开发新型催化剂至关重要.
  • 目前的方法受到繁的蛋白质表达和选的限制.
  • 了解序列-结构-功能关系是关键的,但具有挑战性.

研究的目的:

  • 开发和测试一个高吞吐量的in silico管道,用于预测蛋白质功能.
  • 加速新型蛋白质催化剂的设计和工程.
  • 通过使用真菌黄素依赖的单氧酶进行管道的基准测试.

主要方法:

  • 使用AlphaFold2进行结构预测和快速里埃变换对接.
  • 开发了一种用于in silico选的序列结构功能管道.
  • 采用集体决策树模型和可解释AI用于序列函数建模.

主要成果:

  • 管道预测对enantioselectivity和反应性与实验数据的相关性很好.
  • 使用人工智能识别了控制蛋白质酶选择性和反应性的关键残留物.
  • 与实验验证站点对比验证的已确定的残留物.

结论:

  • 在 silico 管道有效地加速蛋白质工程的努力.
  • 这种方法可以探索用于催化剂设计的庞大的序列景观.
  • 开发的管道为从序列数据中获得信息的蛋白质工程提供了一个框架.