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関連する概念動画

Conserved Binding Sites01:49

Conserved Binding Sites

5.2K
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...
5.2K
RNA Structure01:23

RNA Structure

79.2K
Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
79.2K
RNA Stability01:53

RNA Stability

35.8K
Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
35.8K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

46.0K
VSEPR Theory for Determination of Electron Pair Geometries
46.0K
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

15.1K
The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
15.1K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

5.6K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
5.6K

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Updated: Feb 9, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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RNA-低分子結合部位予測における計算的進歩

Lang Yang1, Zou Yan1, Yanhui Liu1

  • 1School of Physics, Guizhou University, Guiyang, Guizhou 550000, China.

Progress in biophysics and molecular biology
|February 7, 2026
PubMed
まとめ

RNA標的薬の開発に不可欠なRNA-リガンド結合部位を予測するための計算手法が進歩しています。このレビューでは、予測の課題を克服するための、機械学習から大規模言語モデルまでの進化する戦略をカバーしています。

科学分野:

  • 生化学および分子生物学
  • 計算生物学および化学情報学
  • 創薬および医薬品化学

背景:

  • RNA-低分子相互作用は細胞プロセスに不可欠であり、有望な治療標的を表します。
  • RNAの柔軟性、動的な結合部位、構造データの不足により、RNA結合分子の発見は困難です。
  • 計算アプローチは、これらの相互作用を予測するために不可欠です。

研究 の 目的:

  • RNA-リガンド結合部位予測のための計算戦略の進化をレビューすること。
  • マルチモーダル特徴量の統合と分野における現在の課題を強調すること。
  • 正確で一般化可能なRNA標的薬物発見のための将来の方向性を議論すること。

主な方法:

  • 統計モデルから機械学習(ML)および深層学習(DL)フレームワークへの進化。
  • 配列、構造、エネルギー、トポロジーデータの統合。
  • 配列ベースのパターン認識とマルチモーダルモデリングのための大規模言語モデル(LLM)の適用。

主要な成果:

  • 機械学習/深層学習モデルは、予測精度の向上に多様なデータ型を組み込んでいます。
  • 大規模言語モデルは、長距離の配列依存性と文脈情報を捉える能力を向上させます。
キーワード:
結合部位同定計算予測大規模言語モデル機械学習/深層学習RNA-リガンド相互作用

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An Assay for Quantifying Protein-RNA Binding in Bacteria
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An Assay for Quantifying Protein-RNA Binding in Bacteria

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関連する実験動画

Last Updated: Feb 9, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
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Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

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  • 配列情報と構造情報を組み合わせたマルチモーダルアプローチが有望視されています。
  • 結論:

    • 計算戦略は、RNA-リガンド結合部位予測を大幅に進歩させました。
    • LLMを含む多様なデータモダリティの統合は、既存の課題を克服するための鍵となります。
    • 将来の研究は、薬物発見を加速するために、精度、一般化可能性、解釈可能性に焦点を当てるべきです。