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BRENDA, the enzyme database: updates and major new developments

BRENDA, the enzyme database: updates and major new developments Nucleic Acids Research, 2004, Vol. 32, Database issue D431±D433 DOI: 10.1093/nar/gkh081 BRENDA, the enzyme database: updates and major new developments Ida Schomburg, Antje Chang, Christian Ebeling, Marion Gremse, Christian Heldt, Gregor Huhn and Dietmar Schomburg* University of Cologne, Institute of Biochemistry, Zu È lpicher Straûe 47, 50674 Ko È ln, Germany Received September 11, 2003; Revised and Accepted October 3, 2003 ABSTRACT progress of projects of structural and functional genomics and metabolomics, the systematic collection, accessibility and BRENDA (BRaunschweig ENzyme DAtabase) repre- processing of enzyme data becomes even more important in sents a comprehensive collection of enzyme and order to analyse and understand biological processes. metabolic information, based on primary literature. BRENDA, a protein function database (2) contains a huge The database contains data from at least 83 000 dif- amount of enzymic and metabolic data and is updated and ferent enzymes from 9800 different organisms, clas- evaluated by extracting information from the primary litera- ture. Since 2002 the annotation speed has been tripled to 1000 si®ed in ~4200 EC numbers. BRENDA includes EC numbers per year. biochemical and molecular information on classi®- Major developments in the past few years were the ongoing cation and nomenclature, reaction and speci®city, conversion from an EC number/organism-speci®c to a protein- functional parameters, occurrence, enzyme struc- molecule-speci®c database. Furthermore, the presentation and ture, application, engineering, stability, disease, the advanced search engine via the world wide web was isolation and preparation, links and literature refer- improved. Tools like an EC browser, the taxonomy browser ences. The data are extracted and evaluated from and a sequence-based search engine were integrated. ~46 000 references, which are linked to PubMed as BRENDA now provides the opportunity to search for long as the reference is cited in PubMed. In the past substructures of ligands and a thesaurus of those chemical year BRENDA has undergone major changes includ- compounds that are involved in enzyme reactions. In terms ing a large increase in updating speed with >50% of of systematic access and analysis of data, a controlled all data updated in 2002 or in the ®rst half of 2003, vocabulary for organism-speci®c information, i.e. intracellular localization and enzyme source, was established. the development of a new EC-tree browser, a taxonomy-tree browser, a chemical substructure search engine for ligand structure, the development CONTENT OF BRENDA of controlled vocabulary, an ontology for some BRENDA represents a comprehensive relational database information ®elds and a thesaurus for ligand containing all enzymes classi®ed according to the EC system names. The database is accessible free of charge of the Enzyme Nomenclature Committee (IUBMB) (3). This to the academic community at http://www.brenda. classi®cation is based on the type of reaction (e.g. oxidation, uni-koeln.de. reduction, hydrolysis, group transfer) catalysed by the enzyme. In contrast to other databases, BRENDA is not limited to a INTRODUCTION speci®c aspect of the enzyme or to a speci®c organism. It The development of BRENDA was begun in 1987 at the covers organism-speci®c information on functional and German National Research Center for Biotechnology (GBF) molecular properties, enzyme names, catalysed reaction, and continues at the Cologne University Bioinformatics occurrence, sequence, kinetics, substrates/products, inhibitors, Centre. Initially, BRENDA was published as a series of cofactors, activators, structure and stability. books (1). Since 1998 all data have been presented in a Presently, BRENDA holds information on 4200 EC relational database system with access free to the academic numbers, which represent more than 83 000 different enzyme community at http://www.brenda.uni-koeln.de. Commercial molecules. The data in BRENDA are continuously updated by users are required to purchase a licence. manual extraction of relevant parameters from publications Enzymes represent the largest and most diverse group of all searched in the literature databases, i.e. PubMed (4) and proteins, catalysing all chemical reactions in the metabolism SciFinder (5), and all entries are checked for internal of all organisms. They play a key role in the regulation of inconsistencies. In addition, automated literature extraction metabolic steps within the cell. With the development and is being developed to provide an almost complete overview of *To whom correspondence should be addressed. Tel: +49 221 470 6440; Fax: +49 221 470 5092; Email: [email protected] The authors wish it to be known that, in their opinion, all authors should be regarded as joint First Authors Nucleic Acids Research, Vol. 32, Database issue ã Oxford University Press 2004; all rights reserved D432 Nucleic Acids Research, 2004, Vol. 32, Database issue Figure 1. Development of BRENDA data content 2001±2003 in some signi®cant data ®elds. the literature. New information ®elds are continuously added organisms are either found in all parts of the body or are as necessary. Figure 1 shows the quantitative increase of restricted to a single tissue. For practical purposes however, entries since 2001 in BRENDA exempli®ed by some signi®- they are frequently isolated from cultured cells which are cant information ®elds (EC number, literature references, derived from normal or cancerous tissues. The Source/Tissue substrates/products, inhibitors, mutants, K value). ®eld of BRENDA comprises terms of tissues, cell lines and cell types from uni- and multicellular organisms. BRENDA has developed its own ontology corresponding to the rules and SEARCH FEATURES formats of the GO Consortium (6), thus providing the ®rst (enzyme source) ontology for all organisms. The tissue tree is BRENDA is stored as a relational database, containing all data divided into four areas: animal, plant, fungi and other source, in 46 tables, enabling different queries. which are each separated into subtrees. The whole body of an The quick search mode provides easy access to the data of animal, for example, is divided into 18 subtrees, i.e. the each information ®eld individually. The search results are skeletal, hematopoietic and visceral systems. Each different displayed in a comprehensive table format and also as a cell type, cancer cell type or cell line is assigned to the tissue compact printable version. The table version includes links to from which it has developed or to which it is related. The a reference-speci®c view, pictures of molecules functioning as BRENDA Tissue Ontology (BTO) numbers are unique for ligands, Gene Ontology (GO) de®nitions (6), PDB entries (7), each term. Most of the terms have de®nitions and synonyms amino acid sequences (8) and cross-references to other included and different relationships are de®ned between databases. terms, like `part of', `develops from', `is a' or simply `is The advanced search mode allows one to combine 25 related to'. different query criteria. In addition to the possibility of restricting the query to a unique organism, the search can be extended to an upper level of a branch of the BRENDA LOCALIZATION taxonomy tree (TaxTree). The BRENDA TaxTree is based on the tree published by The data ®eld localization contains the part of the cell where the the NCBI (4). The TaxTree search allows users to browse and enzyme is located. BRENDA now has a new controlled search for organism names or nodes in the NCBI taxonomy vocabulary in this data ®eld. In cooperation with the GO browser. In addition, a search can be performed on organisms Consortium (6), the BRENDA team is developing a common that are stored only in BRENDA, but do not occur in any shared vocabulary for the Localization terms. The cellular sequence database. Special features show the availability of component terms of GO are arranged in a concise ontology and data for a speci®c organism class or organism in BRENDA. the vocabulary of BRENDA is now consistent with these terms. The ECTree in BRENDA displays the enzyme classi®cation It includes the GO-numbers which are unique for each term and as de®ned by the IUBMB (3). a link leading to the AmiGO tree view of the term of interest. SOURCE/TISSUE LIGANDS The BRENDA team has created a hierarchical ontology for Another essential part of BRENDA is the information on enzyme sources or tissue. The enzymes of multicellular ligands, which function as natural or in vitro substrates/ Nucleic Acids Research, 2004, Vol. 32, Database issue D433 products, inhibitors, activating compounds, cofactors, bound new features are searches within the TaxTree and the inclusion metals, etc. Now ~500 000 enzyme±ligand relationships are of a controlled vocabulary for subcellular localization. stored with more than 46 000 different chemical compounds functioning as ligands. REFERENCES 1. Schomburg,D. and Schomburg,I. (2001) Springer Handbook of Enzymes. BRENDA-LIGAND THESAURUS 2nd edn. Springer, Heidelberg, Germany. 2. Schomburg,I., Chang,A. and Schomburg,D. (2002) BRENDA, enzyme In addition to the systematic name, which accurately describes data and metabolic information. Nucleic Acids Res., 30, 47±49. a chemical compound, trivial names, abbreviations and 3. Webb,E.C., NC-IUBMB. (1992) Enzyme Nomenclature: synonyms are widely used. BRENDA-LIGAND now provides Recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the Nomenclature and a search for all included synonyms of a given compound and, Classi®cation of Enzymes. Academic Press, New York, NY. thus facilitates ®nding all enzyme±ligand-related information. 4. Wheeler,D.L., Church,D.M., Lash,A.E., Leipe,D.D., Madden,T.L., This thesaurus is based on the generation of unique and chiral Pontius,J.U., Schuler,G.D., Schriml,L.M., Tatusova,T.A., Wagner,L. SMILES strings (9,10) for ligand structures in the database. et al. (2001) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res., 29, 11±16. 5. Ridley,D.D. (2002) SciFinder and SciFinder Scholar. J. Wiley & Sons, BRENDA-LIGAND SUBSTRUCTURE SEARCH New York, NY. 6. Ashburner,C.A., Ball,J.A., Blake, D., Botstein,H., Butler,J.M., As most of the ligand structures have now been entered, Cherry,A.P., Davis, K., Dolinski,S.S., Dwight,J.T., Eppig,M.A. et al. chemical substructure searches are possible. BRENDA pro- (2000) Gene Ontology: tool for the uni®cation of biology. Nature Genet., 25, 25±29. vides subgraph matching searches for most of the small 7. Berman,H.M., Westbrook,J., Feng,Z., Gillilan,G., Bhat,T.N., Weissig,H., molecules functioning as ligands, using a molecular editor Shindyalov,I.N. and Bourne,P.E. (2000) The Protein Data Bank. (11). Nucleic Acids Res., 28, 235±242. In order to achieve rapidity and high precision, the search 8. Boeckmann,B., Bairoch,A., Apweiler,R., Blatter,M., Estreicher,A., consists of two steps. The ®rst step, used as a pre®lter, is the Gasteiger,E., Martin,M.J., Michoud,K., O'Donovan,C., Phan,I. et al. (2003) The Swiss-Prot protein knowledgebase and its supplement very fast ®ngerprint scan (12) of all structures in the database. TrEMBL in 2003. Nucleic Acids Res., 31, 365±370. In the second step all found structures are tested for subgraph 9. Weininger,D. (1988) SMILES, a chemical language and information matching by a module for Maximum Common Substructure system. 1. Introduction to methodology and encoding rules. J. Chem. Inf. searches (12). Comput. Sci., 28, 31±36. The substructure to search can be transferred from any 10. Weininger,D., Weininger,A. and Weininger,J. (1989) SMILES. 2. Algorithm for generation of unique SMILES notation. J. Chem. Inf. ligand search or can be uploaded in several formats and edited Comput. Sci., 29, 97±101. by a structure sketch tool. 11. Csizmadia,P. (2000) MarvinSketch and MarvinView: molecule applets for the World Wide Web. In Pombo-Villar,E., Neier,R. and Lin,S.K. (eds), Proceedings of ECSOC-3, The Third International Electronic SUMMARY Conference on Synthetic Organic Chemistry, September 1±30, 1999. MDPI, Basel, pp. 367±369. http://www.mdpi.org/ecsoc-3.htm. BRENDA is a literature-based information system of func- 12. Steinbeck,C., Han,Y., Kuhn,S., Horlacher,O., Luttmann,E. and tional enzyme data and metabolism. It provides various search Willighagen,E. (2003) The Chemistry Development Kit (CDK): An modes for overall or organism-speci®c queries and now open-source java library for chemo- and bioinformatics. J. Chem. Inf. includes a tool for substructure searches of ligands. Additional Comput. Sci., 43, 493±500. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nucleic Acids Research Oxford University Press

BRENDA, the enzyme database: updates and major new developments

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Nucleic Acids Research, 2004, Vol. 32, Database issue D431±D433 DOI: 10.1093/nar/gkh081 BRENDA, the enzyme database: updates and major new developments Ida Schomburg, Antje Chang, Christian Ebeling, Marion Gremse, Christian Heldt, Gregor Huhn and Dietmar Schomburg* University of Cologne, Institute of Biochemistry, Zu È lpicher Straûe 47, 50674 Ko È ln, Germany Received September 11, 2003; Revised and Accepted October 3, 2003 ABSTRACT progress of projects of structural and functional genomics and metabolomics, the systematic collection, accessibility and BRENDA (BRaunschweig ENzyme DAtabase) repre- processing of enzyme data becomes even more important in sents a comprehensive collection of enzyme and order to analyse and understand biological processes. metabolic information, based on primary literature. BRENDA, a protein function database (2) contains a huge The database contains data from at least 83 000 dif- amount of enzymic and metabolic data and is updated and ferent enzymes from 9800 different organisms, clas- evaluated by extracting information from the primary litera- ture. Since 2002 the annotation speed has been tripled to 1000 si®ed in ~4200 EC numbers. BRENDA includes EC numbers per year. biochemical and molecular information on classi®- Major developments in the past few years were the ongoing cation and nomenclature, reaction and speci®city, conversion from an EC number/organism-speci®c to a protein- functional parameters, occurrence, enzyme struc- molecule-speci®c database. Furthermore, the presentation and ture, application, engineering, stability, disease, the advanced search engine via the world wide web was isolation and preparation, links and literature refer- improved. Tools like an EC browser, the taxonomy browser ences. The data are extracted and evaluated from and a sequence-based search engine were integrated. ~46 000 references, which are linked to PubMed as BRENDA now provides the opportunity to search for long as the reference is cited in PubMed. In the past substructures of ligands and a thesaurus of those chemical year BRENDA has undergone major changes includ- compounds that are involved in enzyme reactions. In terms ing a large increase in updating speed with >50% of of systematic access and analysis of data, a controlled all data updated in 2002 or in the ®rst half of 2003, vocabulary for organism-speci®c information, i.e. intracellular localization and enzyme source, was established. the development of a new EC-tree browser, a taxonomy-tree browser, a chemical substructure search engine for ligand structure, the development CONTENT OF BRENDA of controlled vocabulary, an ontology for some BRENDA represents a comprehensive relational database information ®elds and a thesaurus for ligand containing all enzymes classi®ed according to the EC system names. The database is accessible free of charge of the Enzyme Nomenclature Committee (IUBMB) (3). This to the academic community at http://www.brenda. classi®cation is based on the type of reaction (e.g. oxidation, uni-koeln.de. reduction, hydrolysis, group transfer) catalysed by the enzyme. In contrast to other databases, BRENDA is not limited to a INTRODUCTION speci®c aspect of the enzyme or to a speci®c organism. It The development of BRENDA was begun in 1987 at the covers organism-speci®c information on functional and German National Research Center for Biotechnology (GBF) molecular properties, enzyme names, catalysed reaction, and continues at the Cologne University Bioinformatics occurrence, sequence, kinetics, substrates/products, inhibitors, Centre. Initially, BRENDA was published as a series of cofactors, activators, structure and stability. books (1). Since 1998 all data have been presented in a Presently, BRENDA holds information on 4200 EC relational database system with access free to the academic numbers, which represent more than 83 000 different enzyme community at http://www.brenda.uni-koeln.de. Commercial molecules. The data in BRENDA are continuously updated by users are required to purchase a licence. manual extraction of relevant parameters from publications Enzymes represent the largest and most diverse group of all searched in the literature databases, i.e. PubMed (4) and proteins, catalysing all chemical reactions in the metabolism SciFinder (5), and all entries are checked for internal of all organisms. They play a key role in the regulation of inconsistencies. In addition, automated literature extraction metabolic steps within the cell. With the development and is being developed to provide an almost complete overview of *To whom correspondence should be addressed. Tel: +49 221 470 6440; Fax: +49 221 470 5092; Email: [email protected] The authors wish it to be known that, in their opinion, all authors should be regarded as joint First Authors Nucleic Acids Research, Vol. 32, Database issue ã Oxford University Press 2004; all rights reserved D432 Nucleic Acids Research, 2004, Vol. 32, Database issue Figure 1. Development of BRENDA data content 2001±2003 in some signi®cant data ®elds. the literature. New information ®elds are continuously added organisms are either found in all parts of the body or are as necessary. Figure 1 shows the quantitative increase of restricted to a single tissue. For practical purposes however, entries since 2001 in BRENDA exempli®ed by some signi®- they are frequently isolated from cultured cells which are cant information ®elds (EC number, literature references, derived from normal or cancerous tissues. The Source/Tissue substrates/products, inhibitors, mutants, K value). ®eld of BRENDA comprises terms of tissues, cell lines and cell types from uni- and multicellular organisms. BRENDA has developed its own ontology corresponding to the rules and SEARCH FEATURES formats of the GO Consortium (6), thus providing the ®rst (enzyme source) ontology for all organisms. The tissue tree is BRENDA is stored as a relational database, containing all data divided into four areas: animal, plant, fungi and other source, in 46 tables, enabling different queries. which are each separated into subtrees. The whole body of an The quick search mode provides easy access to the data of animal, for example, is divided into 18 subtrees, i.e. the each information ®eld individually. The search results are skeletal, hematopoietic and visceral systems. Each different displayed in a comprehensive table format and also as a cell type, cancer cell type or cell line is assigned to the tissue compact printable version. The table version includes links to from which it has developed or to which it is related. The a reference-speci®c view, pictures of molecules functioning as BRENDA Tissue Ontology (BTO) numbers are unique for ligands, Gene Ontology (GO) de®nitions (6), PDB entries (7), each term. Most of the terms have de®nitions and synonyms amino acid sequences (8) and cross-references to other included and different relationships are de®ned between databases. terms, like `part of', `develops from', `is a' or simply `is The advanced search mode allows one to combine 25 related to'. different query criteria. In addition to the possibility of restricting the query to a unique organism, the search can be extended to an upper level of a branch of the BRENDA LOCALIZATION taxonomy tree (TaxTree). The BRENDA TaxTree is based on the tree published by The data ®eld localization contains the part of the cell where the the NCBI (4). The TaxTree search allows users to browse and enzyme is located. BRENDA now has a new controlled search for organism names or nodes in the NCBI taxonomy vocabulary in this data ®eld. In cooperation with the GO browser. In addition, a search can be performed on organisms Consortium (6), the BRENDA team is developing a common that are stored only in BRENDA, but do not occur in any shared vocabulary for the Localization terms. The cellular sequence database. Special features show the availability of component terms of GO are arranged in a concise ontology and data for a speci®c organism class or organism in BRENDA. the vocabulary of BRENDA is now consistent with these terms. The ECTree in BRENDA displays the enzyme classi®cation It includes the GO-numbers which are unique for each term and as de®ned by the IUBMB (3). a link leading to the AmiGO tree view of the term of interest. SOURCE/TISSUE LIGANDS The BRENDA team has created a hierarchical ontology for Another essential part of BRENDA is the information on enzyme sources or tissue. The enzymes of multicellular ligands, which function as natural or in vitro substrates/ Nucleic Acids Research, 2004, Vol. 32, Database issue D433 products, inhibitors, activating compounds, cofactors, bound new features are searches within the TaxTree and the inclusion metals, etc. Now ~500 000 enzyme±ligand relationships are of a controlled vocabulary for subcellular localization. stored with more than 46 000 different chemical compounds functioning as ligands. REFERENCES 1. Schomburg,D. and Schomburg,I. (2001) Springer Handbook of Enzymes. BRENDA-LIGAND THESAURUS 2nd edn. Springer, Heidelberg, Germany. 2. Schomburg,I., Chang,A. and Schomburg,D. (2002) BRENDA, enzyme In addition to the systematic name, which accurately describes data and metabolic information. Nucleic Acids Res., 30, 47±49. a chemical compound, trivial names, abbreviations and 3. Webb,E.C., NC-IUBMB. (1992) Enzyme Nomenclature: synonyms are widely used. BRENDA-LIGAND now provides Recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the Nomenclature and a search for all included synonyms of a given compound and, Classi®cation of Enzymes. Academic Press, New York, NY. thus facilitates ®nding all enzyme±ligand-related information. 4. Wheeler,D.L., Church,D.M., Lash,A.E., Leipe,D.D., Madden,T.L., This thesaurus is based on the generation of unique and chiral Pontius,J.U., Schuler,G.D., Schriml,L.M., Tatusova,T.A., Wagner,L. SMILES strings (9,10) for ligand structures in the database. et al. (2001) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res., 29, 11±16. 5. Ridley,D.D. (2002) SciFinder and SciFinder Scholar. J. Wiley & Sons, BRENDA-LIGAND SUBSTRUCTURE SEARCH New York, NY. 6. Ashburner,C.A., Ball,J.A., Blake, D., Botstein,H., Butler,J.M., As most of the ligand structures have now been entered, Cherry,A.P., Davis, K., Dolinski,S.S., Dwight,J.T., Eppig,M.A. et al. chemical substructure searches are possible. BRENDA pro- (2000) Gene Ontology: tool for the uni®cation of biology. Nature Genet., 25, 25±29. vides subgraph matching searches for most of the small 7. Berman,H.M., Westbrook,J., Feng,Z., Gillilan,G., Bhat,T.N., Weissig,H., molecules functioning as ligands, using a molecular editor Shindyalov,I.N. and Bourne,P.E. (2000) The Protein Data Bank. (11). Nucleic Acids Res., 28, 235±242. In order to achieve rapidity and high precision, the search 8. Boeckmann,B., Bairoch,A., Apweiler,R., Blatter,M., Estreicher,A., consists of two steps. The ®rst step, used as a pre®lter, is the Gasteiger,E., Martin,M.J., Michoud,K., O'Donovan,C., Phan,I. et al. (2003) The Swiss-Prot protein knowledgebase and its supplement very fast ®ngerprint scan (12) of all structures in the database. TrEMBL in 2003. Nucleic Acids Res., 31, 365±370. In the second step all found structures are tested for subgraph 9. Weininger,D. (1988) SMILES, a chemical language and information matching by a module for Maximum Common Substructure system. 1. Introduction to methodology and encoding rules. J. Chem. Inf. searches (12). Comput. Sci., 28, 31±36. The substructure to search can be transferred from any 10. Weininger,D., Weininger,A. and Weininger,J. (1989) SMILES. 2. Algorithm for generation of unique SMILES notation. J. Chem. Inf. ligand search or can be uploaded in several formats and edited Comput. Sci., 29, 97±101. by a structure sketch tool. 11. Csizmadia,P. (2000) MarvinSketch and MarvinView: molecule applets for the World Wide Web. In Pombo-Villar,E., Neier,R. and Lin,S.K. (eds), Proceedings of ECSOC-3, The Third International Electronic SUMMARY Conference on Synthetic Organic Chemistry, September 1±30, 1999. MDPI, Basel, pp. 367±369. http://www.mdpi.org/ecsoc-3.htm. BRENDA is a literature-based information system of func- 12. Steinbeck,C., Han,Y., Kuhn,S., Horlacher,O., Luttmann,E. and tional enzyme data and metabolism. It provides various search Willighagen,E. (2003) The Chemistry Development Kit (CDK): An modes for overall or organism-speci®c queries and now open-source java library for chemo- and bioinformatics. J. Chem. Inf. includes a tool for substructure searches of ligands. Additional Comput. Sci., 43, 493±500.

Journal

Nucleic Acids Research – Oxford University Press

Published: Jan 1, 2004

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