关键字：MECHANISM; CRYSTAL
摘要：A universal theory for predicting the catalytic activity of hydrolytic nanozymes has yet to be developed. Herein, by investigating the polarization and hydrolysis mechanisms of nanomaterials towards amide bonds, carbocation charge was identified as a key electronic descriptor for predicting catalytic activity in amide hydrolysis. Through machine learning correlation analysis and the Sure Independence Screening and Sparsifying Operator (SISSO) algorithm, this descriptor was interpreted to associate with the d-band center and Lewis acidity on the nano- material surface. On this basis, copper nanoparticles (Cu NPs) were discovered to exhibit significant hydrolytic activity. Further, peptidomic analysis and molecular dynamics simulations showed that Cu NPs demonstrated substrate selectivity. In the presence of water molecules, hydrophobic amino acid residues were driven towards the nanomaterial surface by hydrophobic groups of proteins, leading to the preferential hydrolysis of peptide bonds linked to these residues. This study provided a theoretic framework for predicting highly efficient hydrolytic nanozymes with broad potential applications.
卷号：683
期号：-
是否译文：否