BRENDA, the ELIXIR core data resource in 2021: new developments and updates

Abstract

The BRENDA enzyme database (https://www.brenda-enzymes.org), established in 1987, has evolved into the main collection of functional enzyme and metabolism data. In 2018, BRENDA was selected as an ELIXIR Core Data Resource. BRENDA provides reliable data, continuous curation and updates of classified enzymes, and the integration of newly discovered enzymes. The main part contains >5 million data for ∼90 000 enzymes from ∼13 000 organisms, manually extracted from ∼157 000 primary literature references, combined with information of text and data mining, data integration, and prediction algorithms. Supplements comprise disease-related data, protein sequences, 3D structures, genome annotations, ligand information, taxonomic, bibliographic, and kinetic data. BRENDA offers an easy access to enzyme information from quick to advanced searches, text- and structured-based queries for enzyme-ligand interactions, word maps, and visualization of enzyme data. The BRENDA Pathway Maps are completely revised and updated for an enhanced interactive and intuitive usability. The new design of the Enzyme Summary Page provides an improved access to each individual enzyme. A new protein structure 3D viewer was integrated. The prediction of the intracellular localization of eukaryotic enzymes has been implemented. The new EnzymeDetector combines BRENDA enzyme annotations with protein and genome databases for the detection of eukaryotic and prokaryotic enzymes.

Figure 1.

Enzyme summary page for EC 3.4.17.23 providing a quick overview on all aspects of the enzyme. The navigation area on the left side shows the new main categories including the number of entries. The ‘Enzyme-Ligand Interactions’ are expanded to show the included information fields.

Figure 2.

Interpathway links in the pathway maps of phosphoenolpyruvate and pyruvate between the glycolysis on the left and the gluconeogenesis on the right.

Figure 3.

Pathway categories in the overview map and a detailed pathway view. The upper part of this figure shows the interactive overview map with pathway backgrounds colored differently with respect to metabolic roles and categorized as central and energy metabolism, lipid metabolism, amino acid metabolism, nucleotide and cofactor metabolism, carbohydrate metabolism, fermentation and other catabolism as well as xenobiotics and secondary metabolism. The lower part of this figure illustrates the detailed pathway view of the acetyl CoA biosynthesis with the highlighted enzyme node 6.2.1.13-acetate-CoA ligase and the enzyme list on the right side.

Figure 4.

The overview map shows the pathway coverage of Bacillus subtilis including all taxonomically related ranks up to the domain Bacteria whereas the example map shows the enzyme coverage for the sulfate reduction.

Figure 5.

An example of the three different plot types for experimental user data in the acetyl-CoA biosynthesis: (A) circle indicators, recommended for transcriptome and proteome data, since duplicate identifiers can be visualized, e.g. when more than one gene encodes for the same enzyme. (B) bar charts, recommended for metabolome data, since they only support positive data values and only one occurrence of each identifier. (C) label boxes, recommended for transcriptome data where two conditions are given as log2fold-changes and one node represents one dataset. The figure is based on exemplary data to illustrate the visualization.

Figure 6.

The EnzymeDetector annotation overview of Arabidopsis thaliana with the histogram representing the distribution of the confidence scores and the circular note behind the UniProt Sequence ID Q9FMV7 in the fourth line of the table pointing to five different annotations for this sequence.

Figure 7.

The ’Pathways’ section of Arabidopsis thaliana with predicted EC numbers in gray and missing EC numbers in red (page 2).