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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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蛋白质-小分子相互作用预测与蛋白质语言模型的最新进展和未来趋势

Alexander Kroll1, Yvan Rousset1

  • 1Heinrich-Heine-University, Universitätsstraße 1, Düsseldorf, 40225, NRW, Germany.

Current opinion in structural biology
|May 25, 2025
PubMed
概括

蛋白质语言模型 (PLM) 揭示了蛋白质序列中的结构和功能的模式. 将PLM与小分子数据集成,有助于预测药物设计和代谢研究的关键蛋白质-小分子相互作用.

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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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.
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