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関連する概念動画

Nucleic Acid Structure01:25

Nucleic Acid Structure

6.9K
The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...
6.9K
Protein Networks02:26

Protein Networks

4.1K
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,...
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Protein Complex Assembly02:41

Protein Complex Assembly

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Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
10.8K
Protein Organization01:24

Protein Organization

7.0K
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....
7.0K
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

2.6K
Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...
2.6K
Protein-protein Interfaces02:04

Protein-protein Interfaces

13.2K
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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Updated: Sep 9, 2025

RNA Secondary Structure Prediction Using High-throughput SHAPE
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RNA-タンパク質複合体のグラフ学習ベースのスコア付け

Zheng Jiang1, Ye Zhang1, Guipu Yang1

  • 1Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, P. R. China.

Journal of chemical theory and computation
|August 29, 2025
PubMed
まとめ
この要約は機械生成です。

EGARPS+はグラフによるディープラーニングを使用して RNA-タンパク質複合構造をスコア付けし,CNNと統計的潜在能力を上回ります. この新しい方法は,特に柔軟な複合体の予測を改善し,新しい構造の予測を助けます.

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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen
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Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

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Last Updated: Sep 9, 2025

RNA Secondary Structure Prediction Using High-throughput SHAPE
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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen
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科学分野:

  • コンピュータ生物学
  • 構造バイオインフォマティクス
  • 構造生物学における機械学習

背景:

  • 正確なスコア付け機能は,RNA-タンパク質複合体の構造を予測するために不可欠です.
  • 伝統的な方法では 形状の柔軟性で苦労します
  • コンボリューションニューラルネットワーク (CNN) は有望ですが,グラフのディープラーニングはバイオ分子タスクに優れた性能を提供します.

研究 の 目的:

  • RNA-タンパク質複合構造のための新しいグラフ学習ベースのスコアリング機能を開発する.
  • これらの複合体内の分子間および分子内相互作用の評価を強化する.
  • RNA-タンパク質構造の予測の精度と強さを向上させる.

主な方法:

  • 提案されたEGARPS+,等価グラフニューラルネットワークと注意力メカニズムを利用したグラフ学習アルゴリズム.
  • インタフェース表現のための新しいシーケンス,構造,インタラクションの特徴を組み込みました.
  • 総合的な評価のために別々の分子間および分子内モジュールを開発した.

主要な成果:

  • EGARPS+は,拘束されたデータセットと非拘束されたデータセットの両方で,CNNベースの方法と統計的可能性を一貫して上回りました.
  • このモデルは,重要な形状の変化,小さなインターフェース,および低い構造的類似性を持つ複合体に対して優れた性能を示した.
  • EGARPS+はRoseTTAFoldNAとAlphaFold3と統合されたとき,新規RNAタンパク質複合体の予測を向上させた.

結論:

  • グラフ・ディープ・ラーニング,特にEGARPS+は RNA-タンパク質複合構造のスコア付けに強力なアプローチを提供します.
  • 複雑なケースを処理し,既存の予測ツールを改善するモデルの能力は,その重要性を強調しています.
  • 解釈性分析は,RNAとタンパク質の相互作用における保存モチーフと水素結合の重要性を明らかにした.