Literature DB >> 9730924

LIGAND: chemical database for enzyme reactions.

S Goto1, T Nishioka, M Kanehisa.   

Abstract

MOTIVATION: The existing molecular biology databases focus on the sequence and structural aspects of biological macromolecules, i.e. DNAs, RNAs and proteins. However, in order to understand the functional aspects, it is essential to computerize the interaction of these molecules. Furthermore, living cells contain additional molecules, such as metabolic compounds and metal ions, that may also be considered as parts of the basic building blocks of life, but are not well organized in public databases. LIGAND chemical database is our attempt to solve these problems, at least for enzymatic reactions.
RESULTS: LIGAND consists of two sections: ENZYME and COMPOUND. The ENZYME section is an extension of previous studies (Suyama et al. , Comput. Applic. Biosci., 9, 9-15, 1993), and it is a flat-file representation of 3303 enzymes and 2976 enzymatic reactions in the chemical equation format that can be parsed by machine. The COMPOUND section has been newly constructed for information on the nomenclature and chemical structures of compounds. It contains 5383 chemical compounds. Both ENZYME and COMPOUND entries contain rich cross-reference information, most of which is automatically generated by the DBGET/LinkDB system, thus providing the linkage between chemical and biological databases. LIGAND is updated daily, tightly coupled with the KEGG metabolic pathway database, and forms the basis for reconstruction and computation of pathways. AVAILABILITY: LIGAND can be accessed through the DBGET/LinkDB and KEGG systems in the Japanese GenomeNet database service via http://www.genome.ad.jp/. The flat-file format of the LIGAND database can be downloaded by anonymous FTP via ftp://kegg. genome.adjp/molecules/ligand/. CONTACT: goto@kuicr.kyoto-u.ac.jp; nishioka@scl.kyoto-u.ac.jp; kanehisa@kuicr.kyoto-u.ac.jp

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Year:  1998        PMID: 9730924     DOI: 10.1093/bioinformatics/14.7.591

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  24 in total

1.  LIGAND: chemical database of enzyme reactions.

Authors:  S Goto; T Nishioka; M Kanehisa
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  LIGAND: database of chemical compounds and reactions in biological pathways.

Authors:  Susumu Goto; Yasushi Okuno; Masahiro Hattori; Takaaki Nishioka; Minoru Kanehisa
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

3.  Dynamic generation and qualitative analysis of metabolic pathways by a joint database/graph theoretical approach.

Authors:  F Ehrentreich; D Schomburg
Journal:  Funct Integr Genomics       Date:  2003-10-16       Impact factor: 3.410

4.  KDBI: Kinetic Data of Bio-molecular Interactions database.

Authors:  Z L Ji; X Chen; C J Zhen; L X Yao; L Y Han; W K Yeo; P C Chung; H S Puy; Y T Tay; A Muhammad; Y Z Chen
Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

5.  Extracting the hierarchical organization of complex systems.

Authors:  Marta Sales-Pardo; Roger Guimerà; André A Moreira; Luís A Nunes Amaral
Journal:  Proc Natl Acad Sci U S A       Date:  2007-09-19       Impact factor: 11.205

6.  A network-based method for target selection in metabolic networks.

Authors:  R Guimerà; M Sales-Pardo; L A N Amaral
Journal:  Bioinformatics       Date:  2007-04-26       Impact factor: 6.937

7.  Prediction of interaction between small molecule and enzyme using AdaBoost.

Authors:  Bing Niu; Yuhuan Jin; Lin Lu; Kaiyan Fen; Lei Gu; Zhisong He; Wencong Lu; Yixue Li; Yudong Cai
Journal:  Mol Divers       Date:  2009-02-14       Impact factor: 2.943

8.  Protein evolutionary rates correlate with expression independently of synonymous substitutions in Helicobacter pylori.

Authors:  Björn Sällström; Ramy A Arnaout; Wagied Davids; Pär Bjelkmar; Siv G E Andersson
Journal:  J Mol Evol       Date:  2006-04-01       Impact factor: 2.395

9.  Predicting drug-target interaction networks based on functional groups and biological features.

Authors:  Zhisong He; Jian Zhang; Xiao-He Shi; Le-Le Hu; Xiangyin Kong; Yu-Dong Cai; Kuo-Chen Chou
Journal:  PLoS One       Date:  2010-03-11       Impact factor: 3.240

10.  PathExpress update: the enzyme neighbourhood method of associating gene-expression data with metabolic pathways.

Authors:  Nicolas Goffard; Tancred Frickey; Georg Weiller
Journal:  Nucleic Acids Res       Date:  2009-05-27       Impact factor: 16.971

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