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Ligand Binding Sites

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

Ligand Binding Sites

Ligand Binding Sites

Conserved Binding Sites

Conserved Binding Sites

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...

Protein Folding

Protein Folding

Ligand Binding and Linkage

Ligand Binding and Linkage

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...

Ligand Binding and Linkage

Ligand Binding and Linkage

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Updated: Jan 8, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

柔軟なタンパク質-リガンドドッキングと拡散ベースの側鎖パッキング

Runze Zhang^1,2, Xinyu Jiang^1,2, Duanhua Cao^1,3

¹Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.

Proceedings of the National Academy of Sciences of the United States of America

|December 24, 2025

まとめ

この要約は機械生成です。

PackDockは、AIと物理学を使用してタンパク質の柔軟性と相互作用をモデル化する新しいフレームワークであり、強力な化合物とそのユニークなスキャフォールドを特定し、重要な分子変化を明らかにし、創薬を改善します。

キーワード:

機械学習分子ドッキングタンパク質構造予測

さらに関連する動画

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors

Published on: October 26, 2015

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

関連する実験動画

Last Updated: Jan 8, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors

Published on: October 26, 2015

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

科学分野:

計算生物学
構造生物学
創薬

背景:

タンパク質の柔軟性は、生物学的機能と創薬において重要ですが、従来のメソッドではそれを捉えることが困難です。
タンパク質-リガンド相互作用を正確にモデル化するには、動的な構造変化を考慮する必要があります。

研究の目的:

深層学習と物理ベースモデリングを統合した新しいフレームワークであるPackDockを導入すること。
静的モデルの限界に対処し、タンパク質の柔軟性とリガンド誘発性の構造変化を捉えること。

主な方法:

PackDockは、拡散モデル（PackPocket）を使用して、多様な結合ポケットの構造をサンプリングします。
検証には、側鎖パッキング、再ドッキング、およびクロスドッキング実験が含まれました。
このフレームワークは、深層学習と物理ベースシミュレーションを統合しています。

主要な成果:

PackDockは、さまざまな計算実験でタンパク質の柔軟性に関する課題を正常に解決しました。
このフレームワークは、標的タンパク質に対してユニークなスキャフォールドを持つ新しいナノモーラーアフィニティ化合物を特定しました。
リガンド結合によって誘発される主要なアミノ酸の構造変化が解明されました。

結論:

PackDockは、タンパク質のダイナミクスを正確に表現するタンパク質-リガンド相互作用をモデル化するための強力なアプローチを提供します。
このフレームワークは、分子認識メカニズムの理解を深めます。
PackDockは、基本的な生物学的研究と創薬の取り組みを進めるための貴重な視点を提供します。