BRENDA

Unique in quality, depth and coverage of the relevant contents.

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 manually from primary literature, and are complemented by text and data mining, data integration, and prediction algorithms.

The curation process has been designed to ensure a maximum of quality, depth and coverage of the contents of this unique database. Formal and consistency checks are done by an elaborate computational pipeline. All enzymes in BRENDA are classified according to the biochemical reaction catalyzed, and are assigned to the corresponding Enzyme Commission (EC) numbers. Reaction kinetics are described in detail. BRENDA’s intuitive user interface support a wide range of queries such as fast full text search, advanced complex queries or searching via sequence or substructure. Browsing the contents is facilitated by a Taxonomic Tree, an Enzyme class, a Genome or an Ontology explorer.

Learn more about BRENDA applications and search functions on YouTube.

The reaction schema of the cytochrome-c oxidase catalyzed reaction.

Structure

The data sources of BRENDA comprise three main domains: Text mining data, manual annotation and external databases and ontologies.

Organization of BRENDA® contents

The supplementary sources FRENDA (enzyme name & organism), AMENDA (enzyme name & organism & occurence), DRENDA (disease-related enzyme data) and KENDA (kinetic data) complement the BRENDA core by text mining data.

The manually annotated core is based on IUBMB enzyme classes and literature from PubMed. Additionally, the BRENDA tissue ontology (BTO) is linked to the manual annotation.

Cross references to several external databases like UniProt, PDB, MetaCyc, ChEBI, KEGG, EMBL, and the Taxonomy Browser of NCBI further expand BRENDA.

Key features

Enzyme and enzyme-ligand information is obtained from different sources, combined with flexible query systems and evaluation tools.

The data are acquired by manual extraction from primary literature, text and data mining, data integration, and prediction algorithms.

The manually derived core contains >3 million data points about >77,000 enzymes annotated from >150,000 publications.

BRENDA comprises molecular data from more than 30,000 organisms.

Each entry is linked to its publication source and the organism of origin. The entries are supplemented 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 connecting functional enzyme data with their anatomical location.

Word Maps for enzymes generated 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.

BRENDA is the most comprehensive information repository on enzymes with 8,149 EC numbers (January 2021).  Thereof  7,787 EC numbers are considered active while others are preliminary or retired and just kept for documentary purpose.

  • SBML output
  • Web-services
  • More detailed statistics can be obtained here.

Benefits

Access the world’s largest manually curated database on enzyme data (>3 million data points annotated).

Experience BRENDA’s intuitive interface, which supports both proteomic beginners and experts in easily retrieving their data of interest.

Take advantage of all the cross-referenced other major databases like KEGG, UniProt, MetaCyc, EMBL, NCBI, and more.

You may install BRENDA on your local Linux or Windows system.

Find at your fingertips essential information from practically all fields of molecular biology, biochemistry, medicine or biotechnology.

Information downloads

BRENDA Flyer (download)
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)
BRENDA release history (download)

Recent applications

Find below a selection of recent articles reporting about BRENDA applications.

Singh, P.K., et al. (2020) Exploring RdRp–remdesivir interactions to screen RdRp inhibitors for the management of novel coronavirus 2019-nCoV. SAR QSAR Environ. Res. 31, 857–867. PubMed

Khurshid, G., et al. (2020) A cyanobacterial photorespiratory bypass model to enhance photosynthesis by rerouting photorespiratory pathway in C3 plants. Sci. Rep. 10, 20879. PubMed

Bartman, C., et al. (2017) Factors influencing the development of visceral metastasis of breast cancer: A retrospective multi-center study. Breast 31, 66-75. PubMed

Brunk, E., et al. (2016) Systems biology of the structural proteome. BMC Syst. Biol. 10, 26. PubMed

Wei, Y., et al. (2015) Insight into Dominant Cellulolytic Bacteria from Two Biogas Digesters and Their Glycoside Hydrolase Genes. PLoS One 10, e0129921. PubMed

Tagore, S., et al. (2014) Analyzing methods for path mining with applications in metabolomics. Gene 534, 125-138. PubMed

Mayer, G., et al. (2014) Controlled vocabularies and ontologies in proteomics: Overview, principles and practice. Biochim. Biophys. Acta 1844, 98-107. PubMed

Ranjan, S., et al. (2013) Computational approach for enzymes present in Capsicum annuum: A review. Int. J. Drug Dev. & Res. 5, 88-97. Link

New release

BRENDA 2022.2

  • BRENDA comprises now 8331 different enzymes.
  • Design of BRENDA Home has been renewed.

BRENDA 2022.1

  • 428 Enzyme Classes have been updated.

BRENDA 2021.2

Data addition & further updates

  • The structure of the database has improved with respect to loading times.
  • BRENDA Tissue Ontology (BTO) has been updated.

BRENDA 2021.1

Data addition & further updates

  • Gene names are now highlighted by a small DNA symbol in the Synonyms section of enzyme summary pages.
  • BRENDA has been supplemented by a newly classified SARS-Cov-2 enzyme given the BRENDA EC number 3.4.22.B80.
    Papain-like proteinase 2 EC 3.4.22.B50 and papain-like proteinase 1 EC 3.4.22.B14 are additional enzymes related to SARS-Cov-2 with a provisional EC number provided by BRENDA.

BRENDA 2020.2

Data addition & further updates

  • Enzymes referring to COVID-19 and SARS-Cov-2, 3.4.17.23 and 3.4.22.69 have been updated.
  • Enzyme summary pages have been reworked – amongst others with respect to loading times.

BRENDA 2020.1

Data addition & further updates

  • The BRENDA chart of metabolic pathways has been revised again.

BRENDA 2019.2

Data addition & further updates

  • In the current release, BRENDA comprises 7867 EC numbers allotted to seven EC classes. Of these more than 6,280 are active entries, 523 entries are considered preliminary while others are retired and just kept for documentary purpose.
  • 8,659,739 references have been exploited by manual curation or text mining.
  • Users of BRENDA Online or the default local installation will also notice a revised top of the Enzyme Summary Pages and a rearranged left-hand menu providing a direct glance on the amount of data available.
  • BRENDA Online or the default local installation: Chart of metabolic pathways now shows the names for all metabolic pathways. Denominations will be enlarged if necessary and turn to bold font when you mouse-over. Individual pathways are now displayed as parts of a network

BRENDA 2019.1

Data addition & further updates

  • Translocases create a new EC class, EC7.

BRENDA 2018.2

Data addition & further updates

  • The number of EC numbers has increased by 241. Thus, in the current release BRENDA comprises 7,512 EC numbers. Of these about 6,000 are active entries, 509 entries are considered preliminary while others are retired and kept for documentary purpose.
  • For the 2018.2 release 7,482,724 references have been exploited by manual curation or text mining.
  • In addition, the Ligand Structure Search has been enhanced and the Ontology “Chemical entities of biological interest” has been updated.

BRENDA 2018.1 

Updates

  • 479 EC classes have been enhanced by manually curated data
  • Word Maps are now also available for a selection of organisms

BRENDA 2017.2

Data addition & further updates

  • 176 new enzyme classes have been integrated. Now BRENDA comprises 7,271 EC numbers. 951 EC numbers were updated with new manually annotated references and more than 55,000 new data were added in this process. Especially the classes of transferases and oxidoreductases have been enhanced by adding 524 or 212 organisms, respectively.
    Additional data retrieved by text mining led to a further increase of data.
  • BRENDA Tissue Ontology (BTO) has been extended by 59 additional terms, further 263 synonyms, and 53 new definitions.
  • 15 new pathways have been added. 
  • 2,079,383 amino acid sequences of cellular organisms have been added. BRENDA now comprises 9,250,412 amino acid sequences. 

BRENDA 2017.1

New features & updates of the web interface and BRENDA online, respectively:

  • The Enzyme Summary Page has been revised.
  • Most of the newly added pathways are accessible via Pathway Overview for customers using the web interface.

Price request BRENDA

Brenda

Recent applications

Recent BRENDA applications:

Singh, P.K., et al. Exploring RdRp–remdesivir interactions to screen RdRp inhibitors for the management of novel coronavirus 2019-nCoV,SAR QSAR Environ. Res. 31:857–867 (2020).

Khurshid, G., et al. A cyanobacterial photorespiratory bypass model to enhance photosynthesis by rerouting photorespiratory pathway in C3 plants, Sci. Rep. 10:20879 (2020).

Bartman, C., et al., Factors influencing the development of visceral metastasis of breast cancer: A retrospective multi-center study, Breast 31:66-75 (2017).

Brunk, E., et al., Systems biology of the structural proteome, BMC Syst. Biol. 10:26 (2016).

Wei, Y., et al., Insight into Dominant Cellulolytic Bacteria from Two Biogas Digesters and Their Glycoside Hydrolase Genes, PLoS One 10:e0129921 (2015).

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 Flyer (download)
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)

Publications

Schomburg I., Jeske L., Ulbrich M., Placzek S., Chang A., Schomburg D. (2017) The BRENDA enzyme information system – From a database to an expert system. J. Biotechnol. 261:194-206 PubMed

Placzek S., Schomburg I., Chang A., Jeske L., Ulbrich M., Tillack J., Schomburg D. (2017) BRENDA in 2017: new perspectives and new tools in BRENDA. Nucleic Acids Res. 45:D380-D388. Oxford.

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.