open access resource
for quantitative prediction
of nanozyme catalytic activity
Nanozymes are defined as “nanomaterials with enzyme-like characteristics”. Among the currently existing nanozymes, the most common are nanozymes with peroxidase and oxidase activities. Other, more complex hydrolase, catalase, phosphatase, laccase, and superoxide dismutase activities start to appear but are much less presented in the literature.
Due to the high stability, long storage time and stability under various conditions nanozymes have been extensively exploited in cancer theranostics, environmental protection, cytoprotection, biosensing, and other applications, and of major attention is the ability to regulate the catalytic activity of nanomaterials by changing its composition, shape, size, crystal structure, as well as surface chemistry.
The DiZyme resource contains a built-in expandable database of nanozymes with links to original articles, an interactive clickable tool for its visualization, and a machine learning models for various levels of user requests(base, progressive and advanced) capable of predicting catalytic activity represented as the Michaelis-Menten (Km, mM) constant with R2 0.63 and the turnover number of nanozyme (Kcat, s-1) with R2 0.80.
This resource will facilitate the design and optimization of nanomaterials with the desired catalytic activity and open new frontiers for nanozyme design.