関連する実験動画

Updated: Feb 22, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

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複雑なリガンド-金属アーキテクチャを予測するためのハイブリッド計算戦略

Galymzhan Moldagulov1,2, Kisung Lee1, Sanzhar Nurgaliyev1

  • 1Center for Algorithmic and Robotized Synthesis (CARS), Institute for Basic Science (IBS), Ulsan, Republic of Korea.

Angewandte Chemie (International ed. in English)
|February 21, 2026
PubMed
まとめ

この研究では,機械学習 (ML) を用いたハイブリッドコンピューティング方式を導入し,金属-リガンドの協調パターンを予測します. ケンブリッジ構造データベース (CSD) で訓練されたMLアルゴリズムは,多様なリガンドと金属の複雑な協調を正確に予測します.

キーワード:
化学情報学 化学情報学調整モード 調整モード機械学習 (Machine Learning) とは,機械学習 (Machine Learning) とは,機械学習 (Machine Learning) と呼ばれるものです.ニューラルネットワークはニューラルネットワークです.オーガニック・メタリック

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