朱之灵

硕士生导师

所在单位:材料化学教研室

学历:博士研究生

办公地点:材料楼218房间

论文成果

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Machine Learning-Assisted High-Throughput Screening of Nanozymes for Ulcerative Colitis

发布时间:2025-07-14 点击次数:

关键字:GRAPHDIYNE/GRAPHENE HETEROSTRUCTURE; HYDROQUINONE; REDUCTION; GRAPHENE; CATECHOL; O-2; RESORCINOL; CATALYSTS
摘要:The catalytic efficiency of natural enzymes depends on the precise electronic interactions between active centers and cofactors within a three-dimensional (3D) structure. Single-atom nanozymes (SAzymes) attempt to mimic this structure by modifying metal active sites with molecular ligands. However, SAzymes struggle to match the catalytic efficiency of natural enzymes due to constraints in active site proximity, quantity, and the inability to simulate electron transfer processes driven by internal electronic structures of natural enzymes. This study introduces a universal spatial engineering strategy in which molecular ligands are replaced with graphdiyne (GDY) to induce d-pi orbital hybridization with copper nanoparticles (Cu NPs), leading to an asymmetric electron-rich distribution along the longitudinal axis that mimics the local electric field of natural laccase. Moreover, multiple sp bonds within GDY scaffold effectively anchor Cu NPs, facilitating the construction of 3D geometric structure similar to that of natural laccase. An enzymatic activity of 82.53 U mg-1 is achieved, 4.72 times higher than that of natural laccase. By reconstructing both 3D structures and local electric fields of natural enzymes through d-pi orbital hybridization, this approach enhances electron interactions between cofactors, active centers, and substrates, and offers a versatile framework for biomimetic design of nanozymes.
卷号:64
期号:6
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