AtlantECO-KER-IM-2

The ENA Data Hubs Portal provides an interface for the data hubs at ENA, which are workspaces and sets of tools that enable users to share, analyse, visualize, search, and retrieve their sequence data. The data hubs are built on top of ENA infrastructure, utilising the same storage, data, and metadata models. A key feature is the ability for a group of users to collaborate on data, sharing it amongst themselves initially whilst preparing their scholarly publication and coincident public data release (in line with ENA’s data release policy). This differs from ENA’s more-personalized Webin accounts for users. Overall, this supports collaborative researchers and groups to better structure, manage, and prepare their data prior to publication. The portal now supports applications beyond infectious disease, and automated data hub setup and management.

Secondary or specialized metabolites show extraordinary structural diversity and potent biological activities relevant for clinical and industrial applications. The biosynthesis of these metabolites usually starts with the assembly of a core ‘scaffold’, which is subsequently modified by tailoring enzymes to define the molecule’s final structure and, in turn, its biological activity profile. Knowledge about reaction and substrate specificity of tailoring enzymes is essential for understanding and computationally predicting metabolite biosynthesis, but this information is usually scattered in the literature. Here, we present MITE, the Minimum Information about a Tailoring Enzyme database. MITE employs a comprehensive set of parameters to annotate tailoring enzymes, defining substrate and reaction specificity by the expressive reaction SMARTS (Simplified Molecular Input Line Entry System Arbitrary Target Specification) chemical pattern language. Both human and machine readable, MITE can be used as a knowledge base, for in silico biosynthesis, or to train machine-learning applications, and tightly integrates with existing resources. Designed as a community-driven and open resource, MITE employs a rolling release model of data curation and expert review. MITE is freely accessible at https://mite.bioinformatics.nl/.