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Updated: Sep 9, 2025

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
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Published on: August 28, 2019

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新しいグラフニューラルネットワークは,エストロゲン受容体BとPAHの相互作用の結合メカニズムと環境リスクを明らかにする

Ying Ren1, Xuan Wu1, Ziming Xi1

  • 1College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, China.

Environmental pollution (Barking, Essex : 1987)
|August 28, 2025
PubMed
まとめ

新しいAIモデルであるMS-DSGATは,ポリサイクルアロマティック炭化水素 (PAH) がエストロゲン受容体β (ERβ) に結合する方法を正確に予測し,これらの相互作用を誘導する重要な分子特性を特定しています. これはこれらの汚染物質から生じる環境的健康リスクを理解し,軽減するのに役立ちます.

キーワード:
エストロゲン受容体 β機械学習分子ドッキングポリサイクルアロマティック炭化水素

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