EnzymeML – Modelling challenges in enzymology and biocatalysis

Jan Range, Jürgen Pleiss

Designing complex biocatalytic reaction systems is a highly complex task due to the
interdependence of various factors such as the enzymes, reaction conditions, and modeling methods, which affect the choice of a kinetic model and the estimated kinetic parameters. As a result, the reproducibility of enzymatic experiments and the reuse of enzymatic data are challenging. Previously, we have developed the XML-based markup language EnzymeML to enables the storage and exchange of enzymatic data, including reaction conditions, substrate and product time courses, kinetic parameters, and kinetic models.1 Our approach aims to make enzymatic data FAIR (findable, accessible, interoperable, and reusable). EnzymeML serves as a seamless communication channel between experimental platforms, electronic lab notebooks, tools for modeling enzyme kinetics, publication platforms, and enzymatic reaction databases.2 EnzymeML is a valuable tool for investigating kinetic models, and model reduction was performed by a general-purpose framework utilizing JAX.

1. Range, J. et al. EnzymeML—a data exchange format for biocatalysis and enzymology. FEBS J. 289, 5864–5874 (2022).
2. Lauterbach, S. et al. EnzymeML: seamless data flow and modeling of enzymatic data. Nat. Methods 2023 (2023) doi:10.1038/s41592-022-01763-1.

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