title: A novel database of disulfide patterns and its application to the discovery of distantly related homologs.
abstract: Disulfide bonds are conserved strongly among proteins of related structure and function. Despite the explosive growth of protein sequence databases and the vast numbers of sequence search tools, no tool exists to draw relations between the disulfide patterns of homologous proteins. We present a comprehensive database of disulfide bonding patterns and a search method to find proteins with similar disulfide patterns. The disulfide database was constructed using disulfide annotations extracted from SwissProt, and was expanded significantly from 16,736 to 94,499 disulfide-containing domains by an inference method that combines SwissProt annotations with Pfam multiple alignments. To search the database, we define a disulfide description, called the disulfide signature, which encodes both spacings between cysteine residues and cysteine connectivity. A web tool was developed that allows users to search for related disulfide patterns and for subpatterns resulting from the removal of one or more disulfides from the pattern. We explore the possibility of using disulfide pattern conservation to identify protein homologs that are undetectable by PSI-BLAST. Examples include the homology between a sea anemone antihypertensive/antiviral protein and a sea anemone neurotoxin, and the homology between tick anticoagulant peptide and bovine trypsin inhibitor. In both examples, there is a clear structural similarity and a functional relationship. We used the database to find structural homologs for the Cripto CFC domain. The identification of a von Willebrand Factor C (VWFC)-like domain agrees with its functional role and explains mutation data. We believe that the rapid increase in structure determinations arising from structural genomics efforts and advances in mass spectrometry techniques will greatly increase the number of disulfide annotations. This information will become a valuable resource for structural and functional annotations of proteins. The availability of a searchable disulfide pattern database will thus provide a powerful new addition to existing homolog discovery methods.
authors.affiliation: Structural Informatics Group, Biogen Inc., 14 Cambridge Center, Cambridge, MA 02142, USA.
authors.forename: Herman W T
authors.initials: HW
authors.lastname: van Vlijmen
authors.forename: Abhas
authors.initials: A
authors.lastname: Gupta
authors.forename: Lakshmi S
authors.initials: LS
authors.lastname: Narasimhan
authors.forename: Juswinder
authors.initials: J
authors.lastname: Singh
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D002417:Cattle; D019295:Computational Biology; D030562:Databases, Protein; D004220:Disulfides / Q000737:chemistry*; D019143:Evolution, Molecular; D007473:Ion Channels / Q000037:antagonists & inhibitors; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009363:Neoplasm Proteins / Q000737:chemistry; D009498:Neurotoxins / Q000737:chemistry; D011480:Protease Inhibitors / Q000737:chemistry; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*; D017385:Sequence Homology; D012984:Software
chemical_list: D004220:Disulfides; D007473:Ion Channels; D009363:Neoplasm Proteins; D009498:Neurotoxins; D011480:Protease Inhibitors; D011506:Proteins