title: Prediction of novel archaeal enzymes from sequence-derived features.
abstract: The completely sequenced archaeal genomes potentially encode, among their many functionally uncharacterized genes, novel enzymes of biotechnological interest. We have developed a prediction method for detection and classification of enzymes from sequence alone (available at http://www.cbs.dtu.dk/services/ArchaeaFun/). The method does not make use of sequence similarity; rather, it relies on predicted protein features like cotranslational and posttranslational modifications, secondary structure, and simple physical/chemical properties.
authors.affiliation: Center for Biological Sequence Analysis, BioCentrum-DTU, The Technical University of Denmark, DK-2800 Lyngby, Denmark.
authors.forename: Lars Juhl
authors.initials: LJ
authors.lastname: Jensen
authors.forename: Marie
authors.initials: M
authors.lastname: Skovgaard
authors.forename: Søren
authors.initials: S
authors.lastname: Brunak
mesh_terms: D020816:Amino Acid Motifs; D000595:Amino Acid Sequence; D001105:Archaea / Q000201:enzymology*; D019295:Computational Biology / Q000379:methods*; D004798:Enzymes / Q000737:chemistry* / Q000145:classification*; D006031:Glycosylation; D016571:Neural Networks, Computer; D010802:Phylogeny; D017433:Protein Structure, Secondary; D013329:Structure-Activity Relationship
chemical_list: D004798:Enzymes