Kumar, Ashutosh, Taubitz, Jan, Meyer, Fabian, Imstepf, Nicolas, Peng, Jiaming, Tassano, Erika, Moore, Charles-1, Lochmann, Thomas, Snajdrova, Radka and Buller, Rebecca (2025) Streamlining enzyme discovery and development through data analysis and computation. Chem Catalysis.

Abstract

Biocatalysis, the use of Nature’s catalysts to perform chemical transformations on organic compounds, is a powerful tool in synthetic chemistry. In this context, the identification of enzymes which accept non-natural substrates is a key step to develop biocatalysts for anthropogenic applications. However, detecting enzymatic reaction products using analytical approaches such as LC-MS can be a complex task, especially when testing numerous putative substrates simultaneously. This complexity becomes even more prominent when evaluating CH-activating enzymes like Fe(II)/α-ketoglutarate dependent dioxygenases, which follow a radical reaction mechanism and are capable of following multiple reaction pathways leading to a variety of products. The complex nature of these reactions requires a data-driven strategy to detect both anticipated but also unexpected reaction outcomes, in this way leading to enhanced enzyme discovery and reaction pathway engineering capabilities.

Item Type:	Article
Date Deposited:	26 Aug 2025 00:45
Last Modified:	26 Aug 2025 00:45
URI:	https://oak.novartis.com/id/eprint/56896