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Updated: Feb 23, 2026

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Published on: February 23, 2024

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ディープラーニングと分子ドッキングにより,生物と相互作用するキノロン抗生物質の活性部位を予測する

Wenjun Zhang1, Wenjing Zhang1, Chenyang Dong1

  • 1Key Laboratory of Integrated Regulation and Resources Development on Shallow Lakes of Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China.

Aquatic toxicology (Amsterdam, Netherlands)
|February 21, 2026
PubMed
まとめ

ディープラーニングモデルは,キノロン (QN) 抗生物質の活性を正確に予測し,細菌のDNA修復酵素や神経行動タンパク質などの標的を特定します. これは環境リスクを評価し,より安全な医薬品を開発するのに役立ちます.

キーワード:
バインディングサイトバイオアッセイ バイオアッセイディープラーニングとは,ディープラーニングです.分子ドッキングです.キノロン系抗生物質 キノロン系抗生物質

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