Enzyme Annotation and Metabolic Reconstruction Using KEGG

  • Minoru KanehisaEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1611)


KEGG is an integrated database resource for linking sequences to biological functions from molecular to higher levels. Knowledge on molecular functions is stored in the KO (KEGG Orthology) database, while cellular- and organism-level functions are represented in the PATHWAY and MODULE databases. Genes in the complete genomes, which are stored in the GENES database, are given KO identifiers by the internal annotation procedure, enabling reconstruction of KEGG pathways and modules for interpretation of higher-level functions. This is possible because all the KEGG pathways and modules are represented as networks of KO nodes. Here we present knowledge-based prediction methods for functional characterization of amino acid sequences using the KEGG resource. Specifically we show how the tools available at the KEGG website including BlastKOALA and KEGG Mapper can be utilized for enzyme annotation and metabolic reconstruction.


KEGG pathway map KEGG module KEGG Mapper Genome annotation Pathway analysis EC number 



This work was partially supported by the National Bioscience Database Center of the Japan Science and Technology Agency. The computational resource for developing and servicing KEGG is provided by the Bioinformatics Center, Institute for Chemical Research, Kyoto University.


  1. 1.
    Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M (2016) KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res 44:D457–D462CrossRefPubMedGoogle Scholar
  2. 2.
    McDonald AG, Tipton KF (2014) Fifty-five years of enzyme classification: advances and difficulties. FEBS J 281:583–592CrossRefPubMedGoogle Scholar
  3. 3.
    Ogata H, Goto S, Fujibuchi W, Kanehisa M (1998) Computation with the KEGG pathway database. Biosystems 47:119–128CrossRefPubMedGoogle Scholar
  4. 4.
    Kanehisa M, Sato Y, Morishima K (2016) BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol 428:726–731CrossRefPubMedGoogle Scholar
  5. 5.
    Li W, Godzik A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22:1658–1659CrossRefPubMedGoogle Scholar
  6. 6.
    Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M (2014) Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res 42:D199–D205CrossRefPubMedGoogle Scholar
  7. 7.
    Kanehisa M (2013) Chemical and genomic evolution of enzyme-catalyzed reaction networks. FEBS Lett 587:2731–2737CrossRefPubMedGoogle Scholar
  8. 8.
    Pearson WR (1991) Searching protein sequence libraries: comparison of the sensitivity and selectivity of the Smith-Waterman and FASTA algorithms. Genomics 11:635–650CrossRefPubMedGoogle Scholar
  9. 9.
    Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Suzuki S, Kakuta M, Ishida T, Akiyama Y (2014) GHOSTX: an improved sequence homology search algorithm using a query suffix array and a database suffix array. PLoS One 9:e103833CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Wang JL, Ma KD, Wang YW, Wang HM, Li YB, Zhou S, Chen XR, Kong DL, Guo X, He MX, Ruan ZY (2016) Lentibacillus amyloliquefaciens sp. nov., a halophilic bacterium isolated from saline sediment sample. Antonie Van Leeuwenhoek 109:171–178CrossRefPubMedGoogle Scholar
  12. 12.
    Takami H, Takaki Y, Uchiyama I (2002) Genome sequence of Oceanobacillus iheyensis isolated from the Iheya Ridge and its unexpected adaptive capabilities to extreme environments. Nucleic Acids Res 30:3927–3935CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Institute for Chemical ResearchKyoto UniversityKyotoJapan

Personalised recommendations