Enzyme‐specific profiles for genome annotation: PRIAM

• Published in: Nucleic acids research Vol. 31; no. 22; pp. 6633 - 6639
• Main Authors: Claudel‐Renard, Clotilde, Chevalet, Claude, Faraut, Thomas, Kahn, Daniel
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 15.11.2003; Oxford Publishing Limited (England)
• Subjects: Bacterial Proteins - genetics; Bacterial Proteins - metabolism; Computational Biology - methods; Databases, Genetic; Databases, Protein; Enzymes - genetics; Enzymes - metabolism; Genome; Genome, Bacterial; Life Sciences; Other; Sensitivity and Specificity; Sinorhizobium meliloti; Sinorhizobium meliloti - genetics; Sinorhizobium meliloti - metabolism; Software; Substrate Specificity
• ISSN: 0305-1048; 1362-4962; 1362-4962
• DOI: 10.1093/nar/gkg847

The advent of fully sequenced genomes opens the ground for the reconstruction of metabolic pathways on the basis of the identification of enzyme‐coding genes. Here we describe PRIAM, a method for automated enzyme detection in a fully sequenced genome, based on the classification of enzymes in the ENZYME database. PRIAM relies on sets of position‐specific scoring matrices (‘profiles’) automatically tailored for each ENZYME entry. Automatically generated logical rules define which of these profiles is required in order to infer the presence of the corresponding enzyme in an organism. As an example, PRIAM was applied to identify potential metabolic pathways from the complete genome of the nitrogen‐fixing bacterium Sinorhizobium meliloti. The results of this automated method were compared with the original genome annotation and visualised on KEGG graphs in order to facilitate the interpretation of metabolic pathways and to highlight potentially missing enzymes.