BRENDA in 2017: new perspectives and new tools in BRENDA

Abstract

The BRENDA enzyme database (www.brenda-enzymes.org) has developed into the main enzyme and enzyme-ligand information system in its 30 years of existence. The information is manually extracted from primary literature and extended by text mining procedures, integration of external data and prediction algorithms. Approximately 3 million data from 83 000 enzymes and 137 000 literature references constitute the manually annotated core. Text mining procedures extend these data with information on occurrence, enzyme-disease relationships and kinetic data. Prediction algorithms contribute locations and genome annotations. External data and links complete the data with sequences and 3D structures. A total of 206 000 enzyme ligands provide functional and structural data. BRENDA offers a complex query tool engine allowing the users an efficient access to the data via different search methods and explorers. The new design of the BRENDA entry page and the enzyme summary pages improves the user access and the performance. New interactive and intuitive BRENDA pathway maps give an overview on biochemical processes and facilitate the visualization of enzyme, ligand and organism information in the biochemical context. SCOPe and CATH, databases for protein structure classification, are included. New online and video tutorials provide online training for the users. BRENDA is freely available for academic users.

Tagger: BeCalm API for rapid named entity recognition

“…These were constructed from Gene Ontology (18), Brenda Tissue Ontology (19), and Disease Ontology (20), identifiers from which are used for normalization of the annotations.…”

Biocatalytic Process Design and Reaction Engineering

“…Nature provides a blueprint for process design by achieving the enormous tasks of complex compound syntheses with high space-, time and stereocontrol. This is due to the great and growing diversity of natural, modified and designed biocatalysts, which have been described, and provide a tremendous knowledge base of renewable and non-toxic catalysts for resource-efficient biotransformations 8 . Biocatalysts are also versatile with respect to solvents as organic synthetic reactions in biological cells can be achieved in aqueous or membrane environments and no organic solvents are needed, thereby putting biocatalysis in an excellent position for a paradigm change of solvent use in organic synthesis 9 .…”

Modelling and multiobjective optimization for simulation of cyanobacterial metabolism

“…Candidate enzymes are identified from the genome annotation, and potential biochemical reactions catalysed by those enzymes are retrieved from biochemical databases such as KEGG (Kanehisa and Goto, 2000;Kanehisa et al, 2017), BRENDA (Schomburg et al, 2000;Placzek et al, 2017) or MetaCyc among others. This step can be carried out manually or by using automated tools (Hamilton and Reed, 2014).…”

“…Nonenzymatic (spontaneous) reactions reported in Synechococcus' metabolism were added as well. Also, EC numbers and stoichiometry assigned to the whole set of reactions were verified with databases such as KEGG (Kanehisa and Goto, 2000;Kanehisa et al, 2016Kanehisa et al, , 2017, BRENDA (Schomburg et al, 2000;Placzek et al, 2017) and MetaCyc and reviewing state-of-the-art literature. Reaction reversibility was also verified, and when no conclusive irreversibility evidence was reported, reactions were set to be reversible.…”

“…Biochemical databases containing information about reactions, genes, proteins, enzymes and molecules involved in metabolic processes, are widely used for this purpose. KEGG (Kanehisa and Goto, 2000; Kanehisa et al, 2016Kanehisa et al, , 2017, BRENDA (Schomburg et al, 2000;Placzek et al, 2017), or ChEBI (Hastings et al, 2013) are among the most popular. Information can also be gathered from available literature (reference books and journal articles), physiological experimental datasets or genomic and phylogenetic data.…”