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Updated: Jul 18, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

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TrGPCR:基于动态深度转移学习的GPCR-利干结合亲和力预测

Yaoyao Lu, Runhua Zhang, Tengsheng Jiang

    IEEE journal of biomedical and health informatics
    |August 23, 2023
    PubMed
    概括

    这项研究引入了TrGPCR,这是一种深度转移学习方法,用于预测G蛋白结合受体 (GPCR) 连接体结合亲和力. 它通过使用二级结构克服了数据的局限性,并提高了对现有模型的预测准确性.

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    Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions06:50

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    Parallel Interrogation of β-Arrestin2 Recruitment for Ligand Screening on a GPCR-Wide Scale using PRESTO-Tango Assay09:03

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    The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
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