Toward Reproducible Enzyme Modeling with Isothermal Titration Calorimetry

Nucleic Acid-based Enzyme Cascades-Current Trends and Future Perspectives

The natural micro- and nanoscale organization of biomacromolecules is a remarkable principle within living cells, allowing for the control of cellular functions by compartmentalization, dimensional diffusion and substrate channeling. In order to explore these biological mechanisms and harness their potential for applications such as sensing and catalysis, molecular scaffolding has emerged as a promising approach. In the case of synthetic enzyme cascades, developments in DNA nanotechnology have produced particularly powerful scaffolds whose addressability can be programmed with nanometer precision. In this minireview, we summarize recent developments in the field of biomimetic multicatalytic cascade reactions organized on DNA nanostructures. We emphasize the impact of the underlying design principles like DNA origami, efficient strategies for enzyme immobilization, as well as the importance of experimental design parameters and theoretical modeling. We show how DNA nanostructures have enabled a better understanding of diffusion and compartmentalization effects at the nanometer length scale, and discuss the challenges and future potential for commercial applications.

Orthogonal protein decoration of DNA nanostructures based on SpyCatcher-SpyTag interaction

We present an efficient and readily applicable strategy for the covalent ligation of proteins to DNA origami by using the SpyCatcher-SpyTag (SC-ST) connector system. This approach showed orthogonality with other covalent connectors and has been used exemplarily for the immobilization and study of stereoselective ketoreductases to gain insight into the spatial arrangement of enzymes on DNA nanostructures.

On the reproducibility of enzyme reactions and kinetic modelling

Enzyme reactions are highly dependent on reaction conditions. To ensure reproducibility of enzyme reaction parameters, experiments need to be carefully designed and kinetic modeling meticulously executed. Furthermore, to enable quality control of enzyme reaction parameters, the experimental conditions, the modeling process as well as the raw data need to be reported comprehensively. By taking these steps, enzyme reaction parameters can be open and FAIR (findable, accessible, interoperable, re-usable) as well as repeatable, replicable and reproducible. This review discusses these requirements and provides a practical guide to designing initial rate experiments for the determination of enzyme reaction parameters and gives an open, FAIR and re-editable example of the kinetic modeling of an enzyme reaction. Both the guide and example are scripted with Python in Jupyter Notebooks and are publicly available (https://fairdomhub.org/investigations/483/snapshots/1). Finally, the prerequisites of automated data analysis and machine learning algorithms are briefly discussed to provide further motivation for the comprehensive, open and FAIR reporting of enzyme reaction parameters.