BRENDA is the most comprehensive information repository on enzymes and enzyme ligand data. The BRENDA enzyme information system has developed into an elaborate system of enzyme and enzyme-ligand information obtained from different sources, combined with flexible query systems and evaluation tools. BRENDA has been developed and is maintained by the Institute of Biochemistry and Bioinformatics at the Technical University of Braunschweig, Germany. Data on enzyme function are extracted directly from the primary literature, text and data mining, data integration, and prediction algorithms.
Formal and consistency checks are done by computer programs. All enzymes in BRENDA are classified according to their biochemical reaction catalyzed. The Enzyme Commission numbers (EC numbers) are clasified by the Enzyme Nomenclature of the IUBMB. Every clasified enzyme is characterized with respect to its catalyzed biochemical reaction. Kinetic properties of the corresponding reactants; i.e., substrates and products are described in detail. BRENDA’s user interface allows different search functions from quick search over full text search up to combined advanced search or searching via sequence or substructure. BRENDA provides also different explorers like Taxonomic Tree, Enzyme class, Genome and Ontology explorer.
Learn more about BRENDA applications and search functions on YouTube.


brenda start page
The user interface entry page of BRENDA.
cytochrome-c oxidase catalyzed reaction
The reaction schema of the cytochrome-c oxidase catalyzed reaction.


The core of BRENDA comprises three main domains: Text mining data, manual annotation and external databases and ontologies.
On top of each of these three domains, an abstract view on its contents is provided.
Organization of BRENDA® contents
The text mining data came from FRENDA (enzyme name & organism), AMENDA (enzyme name & organism & occurence), DRENDA (disease-related enzyme data) and KENDA (kinetic data).
The manual annotation based on IUBMB enzyme classes and literature from PubMed. [column3_3]Additionally the BRENDA tissue ontology (BTO) is linked to the manual annotation.

Several external databases like UniProt, PDB, MetaCyc, ChEBI, KEGG, EMBL, and Taxonomy Browser of NCBI expand BRENDA.[/column3_3]

Key features

Enzyme and enzyme-ligand information obtained from different sources, combined with flexible query systems and evaluation tools.
The information is obtained by manual extraction from primary literature, text and data mining, data integration, and prediction algorithms.
The manually derived core contains 3 million data from 77,000 enzymes annotated from 135,000 literature references.
Molecular data from more than 30,000 organisms is stored.
Each entry is connected to the literature reference and the source organism. They are complemented by information on occurrence, enzyme / disease relationships from text mining, sequences and 3D structures from other databases, and predicted enzyme location and genome annotation.
The human anatomy atlas CAVEman is linked to the BRENDA Tissue Ontology terms providing a connection between anatomical and functional enzyme data.
Word Maps for enzymes obtained from PubMed abstracts highlight application and scientific relevance of enzymes.
The EnzymeDetector genome annotation tool and the reaction database BKM-react including reactions from BRENDA, KEGG and MetaCyc.
Most comprehensive information repository on enzymes with 6,759 EC numbers (September 2015)
  • SBML output
  • web-services
  • More detailed statistics can be obtained here.


Access to the world’s largest manually curated database on enzyme data (>3 million data entries annotated).
Intuitive interface allows data retrieval for proteomic beginners and experts alike.
Cross-referenced to other major databases like KEGG, UniProt, MetaCyc, EMBL, NCBI, and more.
In-house installation for commercial customers.
Essential information for molecular biology, biochemistry, medical and biotechnical research at your fingertips.

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Recent applications

Recent BRENDA® applications:
Brunk, E., et al., Systems biology of the structural proteome, BMC Syst. Biol. 10:26 (2016).
Tagore, S., et al., Analyzing methods for path mining with applications in metabolomics, Gene 534:125-138 (2014).
Mayer, G., et al., Controlled vocabularies and ontologies in proteomics: Overview, principles and practice, Biochim. Biophys. Acta 1844:98-107 (2014).
Ranjan, S., et al., Computational approach for enzymes present in Capsicum annuum: A review, Int. J. Drug Dev. & Res 5:88-97 (2013).

Information downloads

BRENDA statistics (pdf, 84 kB)
BRENDA Tutorial: Introduction (download pdf, 0.6 MB)
More BRENDA Tutorials (here)
BRENDA Exercises (download pdf, 1.7 MB)
BRENDA Video (at YouTube)
See also the BRENDA (entry at Wikipedia)


Chang A., Schomburg I., Placzek S., Jeske L., Ulbrich M., Xiao M., Sensen C.W., Schomburg D. (2015) BRENDA in 2015: exciting developments in its 25th year of existence Nucleic Acids Res. 43:D439-D446. Oxford.

Schomburg I., Chang A., Placzek S., Söhngen C., Rother M., Lang M., Munaretto C., Ulas S., Stelzer M., Grote A. Scheer M., Schomburg D. (2013) BRENDA in 2013: integrated reactions, kinetic data, enzyme function data, improved disease classification: new options and contents in BRENDA. Nucleic Acids Res. 41:764-772. PubMed.

Gremse M., Chang A., Schomburg I., Grote A., Scheer M., Ebeling C., Schomburg D.(2011) The BRENDA Tissue Ontology (BTO): the first all-integrating ontology of all organisms for enzyme sources. Nucleic Acids Res. 39:D507-D513. PubMed.

Barthelmes J., Ebeling C., Chang A., Schomburg I., Schomburg D. (2007) BRENDA, AMENDA and FRENDA: the enzyme information system in 2007. Nucleic Acids Res. 35:D511-D514 PubMed.

Schomburg I., Chang A., Hofmann O., Ebeling C., Ehrentreich F., Schomburg D., (2002) BRENDA: a resource for enzyme data and metabolic information. Trends Biochem. Sci. 27:54-56. PubMed

Schomburg, I., Chang, A., Schomburg, D., (2002) BRENDA, enzyme data and metabolic information. Nucleic Acids Res. 30:47-49. PubMed

Schomburg, D., Schomburg, I. (2001) Springer Handbook of Enzymes. 2nd Ed. Springer, Heidelberg Springer

Schomburg, I., Hofmann, O., Baensch, C., Chang, A., Schomburg, D., (2000) Enzyme data and metabolic information: BRENDA, a resource for research in biology, biochemistry, and medicine. Gene Funct. Dis. 3-4:109-18.