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Updated: Feb 14, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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Dynamic-GLEP: 代表的なクラスAのGPCRにおけるリガンド有効性予測のためのダイナミクス情報に基づくディープラーニングフレームワーク.

Zhiyi Chen1,2, Yongxin Hao2,3, Yuhong Su4

  • 1School of Life Sciences, Nanjing University, 163 Xianlin Avenue, Nanjing 210023, China.

Briefings in bioinformatics
|February 12, 2026
PubMed
まとめ

新しいコンピューティングフレームワークであるDynamic-GLEPは,分子動態を分析することによって,Gタンパク質結合受容体 (GPCRs) に対する薬剤の有効性を正確に予測します. このアプローチは,機能的選択性にとって重要な構造変化を捉えることで,薬剤発見を向上させます.

キーワード:
GPCRリガンドの有効性についてコンフォーマーションアンサンブルは,コンフォーマーションアンサンブルである.ディープラーニングとは,ディープラーニングです.分子ダイナミクス 分子ダイナミクス構造ベースの薬物設計移転学習は学習の移転である.

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