Enzymes suffer from high cost, complex purification, and low stability. Development of low‐cost artificial enzymes of comparative or higher effectiveness is desired. Given its complexity, it is desired to presume their activities prior to experiments. While computational approaches demonstrate success in modeling nanozyme activities, they require assumptions about the system to be made. Machine learning (ML) is an alternative approach towards data‐driven material property prediction achieving high performance even on multicomponent complex systems. Despite the growing demand for customized nanozymes, there is no open access nanozyme database. Here, a user‐friendly expandable database of >300 existing inorganic nanozymes is developed by data collection from >100 articles. Data analysis is performed to reveal the features responsible for catalytic activities of nanozymes, and new descriptors are proposed for its ML‐assisted prediction. A random forest regression (RFR) model for evaluation of nanozyme peroxidase activity is developed and optimized by correlation‐based feature selection and hyperparameter tuning, achieving performance up to R2 = 0.796 for Kcat and R2 = 0.627 for Km. Experiment‐confirmed unknown nanozyme activity prediction is also demonstrated. Moreover, the DiZyme expandable, open‐access resource containing the database, predictive algorithm, and visualization tool is developed to boost novel nanozyme discovery worldwide (https://dizyme.net).

Magnetically controlled enzymatic composites have received much attention for both therapeutic and industrial applications. Until now, such materials have been composed of at least four components: the enzyme, magnetic nanoparticles, their stabilizing components, and an organic or inorganic (or hybrid) matrix as a carrier. However, such compositions affect the magnetic response and the enzymatic activity, and also pose obstacles for intravenous administration, because of regulatory restrictions. Here, we present a methodology for the creation of magnetic bioactive nanocomposites composed of only two biocompatible components: an enzyme and magnetite nanoparticles. A series of magnetic biocomposites with a full set of therapeutical and industrial proteins (carbonic anhydrase, ovalbumin, horseradish peroxidase, acid phosphatase, proteinase, and xylanase) were successfully created by the direct entrapment of the proteins within a sol–gel magnetite matrix specially developed for these aims. The activity of the entrapped enzymes was studied at different temperatures and concentrations, and it was found that they showed remarkable thermal stabilization induced by the ferria matrix. For instance, entrapped carbonic anhydrase catalyzed the decomposition of p-nitrophenylacetate at a temperature of 90 °C, while free enzyme completely loses activity and denaturates already at 70 °C. Magnetic characterization of the obtained biomaterials is provided.

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The paper classifies and generalizes innovative technologies for assessing the competencies and skills of the 21st century students in the education system. Taking into account the requirements of the international academic community, criteria for assessing students' competencies in the context of the formation of functional literacy, the ability to study and evaluate independence, global competence and meta-subject skills (soft skills) are considered. The necessity of ensuring continuity of assessment of students' competencies at the levels of general and higher education, as well as the results of formative assessment as an integrative innovative educational technology for the formation, control and evaluation of educational achievements, is emphasized. The possibilities of formative assessment for the development of meta-subject competencies of students are considered. It contains information on the innovative Evidence-Centered Design competency assessment methodology, which contributes to the further development of control and evaluation activities to ensure reliable and valid assessment of students’ achievements and quality assurance in a competency-based approach.

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Enzymatically active nanocomposites are a perspective class of bioactive materials that finds their application in numerous fields of science and technology ranging from biosensors and therapeutic agents to industrial catalysts. Key properties of such systems are their stability and activity under various conditions, the problems that are addressed in any research devoted to this class of materials. Understanding the principles that govern these properties is critical to the development of the field, especially when it comes to a new class of bioactive systems. Recently, a new class of enzymatically doped magnetite-based sol-gel systems emerged and paved the way for a variety of potent bioactive magnetic materials with improved thermal stability. Such systems already showed themself as perspective industrial and therapeutic agents, but are still under intense investigation and many aspects are still unclear. Here we made a first attempt to describe the interaction of biomolecules with magnetite-based sol-gel materials and to investigate facets of protein structure rearrangements occurring within the pores of magnetite sol-gel matrix using ATR Fourier-transform infrared spectroscopy.

The present study is devoted to the development of a new class recyclable magnetic catalytic nanocomposites for starch hydrolysis. α-Amylase was entrapped within a magnetite-derived xerogel matrix in a course of a room-temperature sol-gel transition, leading to enzyme immobilization within the pores of a rigid magnetic matrix. For hybrid organo-inorganic composites with enzyme mass fractions less than 10 wt %, no enzyme leaching was observed. At 80 °C, the amylase@ferria composite demonstrates catalytic activity on the level of 10 units/mg and the starch hydrolysis rate comparable to free enzyme, while at 90 °C, the activity of amylase@ferria is at least twice higher than that of free amylase as a result of higher thermal stability of the composite. Entrapped amylase showed excellent stability and lost only 9% of its activity after 21 days of storage in a buffer solution, while free enzyme was totally inactivated after 17 days. The material can be used as either a magnetically separable reusable catalyst or a catalytic ceramic coating with at least 10 cycles of use.

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