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Updated: Feb 1, 2026

Exploring Protein-Glycan Interactions: Advances in Nuclear Magnetic Resonance
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化学基因组学语言模型朝着可靠和可解释的化合物-蛋白质相互作用探索方向发展

Takuto Koyama1, Hayato Tsumura1, Ryunosuke Okita2

  • 1Graduate School of Medicine, Kyoto University, 53 Shogoin-Kawaharacho, Sakyo-ku, Kyoto, 606-8507, Japan.

Journal of cheminformatics
|January 31, 2026
PubMed
概括

ChemGLaM是一种新的化学基因组学语言模型,可以准确地预测化合物-蛋白相互作用 (CPI),具有高可靠性和可解释性. 这推动了人工智能驱动的药物发现,通过实现可靠的虚拟查和提供分子洞察力.

关键词:
化合物蛋白相互作用预测深度学习是一种深度学习.药物发现 药物发现语言模型 语言模型

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