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相关概念视频

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

10.6K
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...
10.6K
Conserved Binding Sites01:49

Conserved Binding Sites

4.1K
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...
4.1K
Conservation of Protein Domains02:26

Conservation of Protein Domains

3.0K
3.0K
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

6.6K
Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....
6.6K
Protein and Protein Structure02:15

Protein and Protein Structure

77.3K
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...
77.3K
Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

3.6K
ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
3.6K

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相关实验视频

Updated: May 10, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

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分享重量图框架用于在各种突变类型中全面预测蛋白质稳定性.

Gen Li1, Sijie Yao1, Long Fan1

  • 1Production and R&D Center I of LSS, GenScript (Shanghai) Biotech Co., Ltd., 186 He Dan Road, Pudong New Area, Shanghai 200131, China.

Briefings in bioinformatics
|April 24, 2025
PubMed
概括

UniMutStab准确地预测了来自任何突变类型的蛋白质稳定性变化,包括复杂的多点和单点突变. 这通过使精确的蛋白质修饰成为可能,推进了蛋白质工程和治疗开发.

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的工程.

背景情况:

  • 蛋白质的稳定性对于了解疾病和工业酶功能至关重要.
  • 现有的模型主要针对单点突变,忽视多点和内置突变.
  • 预测复杂突变的稳定性变化是当前方法的挑战.

研究的目的:

  • 开发一种新的计算方法,UniMutStab,能够预测任意突变类型的蛋白质稳定性变化.
  • 克服现有模型的局限性,这些模型主要关注单点突变.
  • 为了提高蛋白质稳定性预测的准确性和范围.

主要方法:

  • UniMutStab使用共享图形卷积网络架构.
  • 它集成了蛋白质语言模型和残留物相互作用网络.
  • 嵌入式边缘重量模块可以更好地结合残留特征和相互作用.

主要成果:

  • 在预测蛋白质稳定性变化方面,UniMutStab超越了现有的方法.
  • 该模型在多个预测任务中展示了强大的概括性.
  • 它准确地预测了单点,多点和indel突变的稳定性变化.
关键词:
深度学习是一种深度学习.多样化的突变变异.蛋白质嵌入 蛋白质嵌入蛋白质的稳定性 蛋白质的稳定性分享重量的共享重量.

更多相关视频

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
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Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

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

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相关实验视频

Last Updated: May 10, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

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Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

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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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结论:

  • UniMutStab提供一种纯粹基于序列的方法来预测任意突变类型.
  • 这种方法显著改善了对蛋白质稳定性变化的预测.
  • 它有可能推进蛋白质工程,个性化治疗和诊断.