title: ELISA: structure-function inferences based on statistically significant and evolutionarily inspired observations.
abstract: The problem of functional annotation based on homology modeling is primary to current bioinformatics research. Researchers have noted regularities in sequence, structure and even chromosome organization that allow valid functional cross-annotation. However, these methods provide a lot of false negatives due to limited specificity inherent in the system. We want to create an evolutionarily inspired organization of data that would approach the issue of structure-function correlation from a new, probabilistic perspective. Such organization has possible applications in phylogeny, modeling of functional evolution and structural determination. ELISA (Evolutionary Lineage Inferred from Structural Analysis, http://romi.bu.edu/elisa) is an online database that combines functional annotation with structure and sequence homology modeling to place proteins into sequence-structure-function "neighborhoods". The atomic unit of the database is a set of sequences and structural templates that those sequences encode. A graph that is built from the structural comparison of these templates is called PDUG (protein domain universe graph). We introduce a method of functional inference through a probabilistic calculation done on an arbitrary set of PDUG nodes. Further, all PDUG structures are mapped onto all fully sequenced proteomes allowing an easy interface for evolutionary analysis and research into comparative proteomics. ELISA is the first database with applicability to evolutionary structural genomics explicitly in mind.
  
  
  BACKGROUND
  The database is available at http://romi.bu.edu/elisa.
authors.affiliation: BioInformatics Program, Boston University, Boston, MA, 02215, USA. borya@bu.edu
authors.forename: Boris E
authors.initials: BE
authors.lastname: Shakhnovich
authors.forename: John M
authors.initials: JM
authors.lastname: Harvey
authors.forename: Steve
authors.initials: S
authors.lastname: Comeau
authors.forename: David
authors.initials: D
authors.lastname: Lorenz
authors.forename: Charles
authors.initials: C
authors.lastname: DeLisi
authors.forename: Eugene
authors.initials: E
authors.lastname: Shakhnovich
mesh_terms: D000595:Amino Acid Sequence; D001426:Bacterial Proteins / Q000737:chemistry / Q000502:physiology; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D030562:Databases, Protein / Q000706:statistics & numerical data*; D019143:Evolution, Molecular; D020407:Internet; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D010802:Phylogeny; D020836:Protein Structure, Quaternary / Q000502:physiology; D017434:Protein Structure, Tertiary / Q000502:physiology; D017386:Sequence Homology, Amino Acid; D013329:Structure-Activity Relationship
chemical_list: D001426:Bacterial Proteins