BRENDA is subject to the terms of the Creative Commons license (CC BY 4.0), is accessible worldwide and can be used free of charge.

Springerverlag published the first of nineteen editions of the "Springer Handbook of Enzymes" in 1990, which contained data on over 3000 EC classes.

[2] In June 2018, BRENDA was included in the prestigious list of Core Data Resources maintained by ELIXIR, a European initiative for digital research infrastructure in biomedicine.

[8] The BRENDA content basically covers organisms of all domains and is geared to the broad interest of the scientific community from different areas of life sciences such as systems biology, biotechnology, medicine and pharmaceuticals.

The EC numbers are part of a system established by the IUBMB that classifies enzymes according to their catalytic activity, i.e. the chemical reaction.

The IUBMB Enzyme Commission has so far defined over 8300 EC numbers in seven main classes, all of which - including the obsolete ones - can be found in BRENDA.

The literature base of the data of an EC number can comprise several hundred publications if it contains medically or industrially relevant and thus well-studied enzymes.

Depending on their role in enzymatic reactions, these are categorized as substrate, product, inhibitor, activator, cofactor or as metals and ions (if their function is not specified in the literature).

These molecules can have different functions, e.g. they can be metabolites of primary metabolism, naturally occurring antibiotics or synthetic compounds used in the development of drugs or pesticides.

In addition to these web browser-based query options, users can obtain the BRENDA data via SOAP-API or SBML download.

The process of integrating new data begins with a manual literature search in PubMed and Scopus and the selection of relevant, qualitative and comprehensive publications.

Due to the manual and selective annotation process, the literature base and the associated amount of data in BRENDA is quantitatively limited.

In 2006, a computer-aided information retrieval function (text mining) was established to expand the manually curated data core.

Computer-aided methods search the specialist literature available online and automatically annotate certain information in the corresponding data categories.