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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

10.9K
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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Protein Families02:47

Protein Families

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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...
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Conserved Binding Sites01:49

Conserved Binding Sites

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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...
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Conservation of Protein Domains02:26

Conservation of Protein Domains

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Protein and Protein Structure02:15

Protein and Protein Structure

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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 17, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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使用深度学习进行蛋白质远程同质检测和结构调整.

Tymor Hamamsy1, James T Morton2,3, Robert Blackwell4

  • 1Center for Data Science, New York University, New York, NY, USA.

Nature biotechnology
|September 7, 2023
PubMed
概括
此摘要是机器生成的。

我们开发了两个深度学习方法TM-Vec和DeepBLAST,以识别结构相似的蛋白质,即使其序列相似性很低. 这些工具改善了用于生物技术应用的蛋白质对齐.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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相关实验视频

Last Updated: Jul 17, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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科学领域:

  • 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.
  • 蛋白质结构预测 蛋白质结构预测

背景情况:

  • 精确的蛋白质对齐对于理解生物技术中的序列结构功能关系至关重要.
  • 现有的方法难以识别具有较低序列相似性的同类蛋白质.
  • 需要先进的计算工具来弥合这一差距.

研究的目的:

  • 开发新的深度学习方法来识别和对准具有低序列相似性的蛋白质.
  • 为了提高生物技术应用的远程同源蛋白质的发现.

主要方法:

  • 开发了TM-Vec用于直接从蛋白质序列对中预测TM-score (结构相似性的衡量标准).
  • 开发了DeepBLAST,通过识别同源区域,仅使用序列信息来结构调整蛋白质.
  • 在各种蛋白质数据集上训练并验证了这两种方法.

主要成果:

  • TM-Vec可以准确地预测结构相似性,而无需进行中间结构计算.
  • DeepBLAST的性能优于传统的序列对齐方法,并且与基于结构的对齐性能相匹配.
  • 与最先进的方法相比,这两种方法都证明了远程同源蛋白质的优异识别.

结论:

  • TM-Vec和DeepBLAST为蛋白质序列对齐提供了强大的深度学习解决方案,特别是对于与远距离相关的蛋白质.
  • 这些方法有助于在生物技术中利用序列结构功能关系.
  • 开发的工具可以在大型生物序列数据库中增强蛋白质注释和发现.