title: Ab initio modeling led annotation suggests nucleic acid binding function for many DUFs.
abstract: Expansions of sequence databases driven by new sequencing technology continue apace. These result in a continuous supply of protein sequences and domains that cannot be straightforwardly annotated by simple homology methods. For these, structure-based function prediction may contribute to an improved annotation. Here, short Domains of Unknown Function (DUFs) are ab initio modeled with ROSETTA and screened for likely nucleic acid binding function. Thirty-two DUFs are thereby predicted to have a nucleic acid binding function. In most cases, additional evidence supporting that function could be obtained from structure comparison, domain architectures, distant evolutionary relationships, genome context or protein-protein interaction data. These predictions contribute to the function annotation of thousands of proteins.
authors.affiliation: University of Liverpool, Institute of Integrative Biology, United Kingdom. drigden@liv.ac.uk
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Rigden
mesh_terms: D030562:Databases, Protein; D009696:Nucleic Acids / Q000378:metabolism; D011485:Protein Binding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism
chemical_list: D009696:Nucleic Acids; D011506:Proteins