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相关概念视频

Intrinsically Disordered Proteins02:18

Intrinsically Disordered Proteins

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Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...
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Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

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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...
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Leaky Scanning02:28

Leaky Scanning

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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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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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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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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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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DR-BERT:一种蛋白质语言模型,用于注释无序的区域.

Ananthan Nambiar1, John Malcolm Forsyth2, Simon Liu2

  • 1Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, Urbana, IL 61801, USA.

Structure (London, England : 1993)
|May 3, 2024
PubMed
概括

我们开发了DR-BERT,这是一种新的蛋白质语言模型,用于准确预测内在无序区域 (IDR). 通过利用在预训练期间学到的上下文信息,DR-BERT的表现优于现有方法.

关键词:
国内发展计划 (IDP) 是一个.这是一个IDR IDR.深度学习是一种深度学习.这是一种混乱的混乱,一种混乱的混乱.机器学习是机器学习.蛋白质语言模型蛋白质结构预测 蛋白质结构预测

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A Protocol for Computer-Based Protein Structure and Function Prediction
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科学领域:

  • 计算生物学是一种计算生物学.
  • 蛋白质的生物信息学
  • 在基因组学中的机器学习.

背景情况:

  • 内在无序区域 (IDR) 缺乏刚性结构,但对于蛋白质功能至关重要,例如调解相互作用.
  • 准确的IDR计算注释对于理解细胞机制至关重要.

研究的目的:

  • 介绍DR-BERT,一个紧的蛋白质语言模型,用于准确的IDR预测.
  • 通过使用基准数据集对现有方法进行DR-BERT性能评估.

主要方法:

  • DR-BERT 在未注释的蛋白质上进行了预训练.
  • 该模型经过训练,可以在没有明确的进化或生物物理数据的情况下预测IDR.
  • 对蛋白质内在障碍 (CAID) 和CAID 2数据集的批判性评估进行了绩效评估.

主要成果:

  • 在CAID数据集上,DR-BERT显示了与现有的IDR预测工具相比的显著改进.
  • 该模型在CAID 2数据集中的四个测试案例中的两个中表现优于竞争对手.
  • 在剩余的CAID 2测试案例中,DR-BERT保持了竞争力.

结论:

  • DR-BERT的表现源于在预训练期间学到的信息及其对上下文信息利用的能力.
  • 该模型为IDR注释提供了一个高度准确和高效的方法.