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Updated: Jan 13, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Published on: January 26, 2024

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基于分子结构的机器学习模型来预测 (Pro) cathepsin-glycosaminoglycan结合的自由能量

Krzysztof K Bojarski1,2, Patrick K Quoika2, Martin Zacharias2

  • 1Department of Physical Chemistry, Gdansk University of Technology, Narutowicza 11/12, Gdansk, Poland.

Computational and structural biotechnology journal
|January 8, 2026
PubMed
概括

机器学习模型准确地预测了 cathepsins 和 glycosaminoglycans (GAGs) 之间的结合自由能量. 这种方法加速了对药物设计中的蛋白质-GAG相互作用的理解.

关键词:
具有约束力的能量计算 (MM-GBSA)葡萄糖氨基甘 (GAG) 是一种机器学习 (ML) 是指机器学习.分子动力学 (MD) 是指分子动力学神经网络 (NN) 神经网络 (NN) 是一个神经网络.定量结构与活动关系 (QSAR)

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