title: Predicting protein function from sequence and structural data.
abstract: When a protein's function cannot be experimentally determined, it can often be inferred from sequence similarity. Should this process fail, analysis of the protein structure can provide functional clues or confirm tentative functional assignments inferred from the sequence. Many structure-based approaches exist (e.g. fold similarity, three-dimensional templates), but as no single method can be expected to be successful in all cases, a more prudent approach involves combining multiple methods. Several automated servers that integrate evidence from multiple sources have been released this year and particular improvements have been seen with methods utilizing the Gene Ontology functional annotation schema.
authors.affiliation: EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. watson@ebi.ac.uk
authors.forename: James D
authors.initials: JD
authors.lastname: Watson
authors.forename: Roman A
authors.initials: RA
authors.lastname: Laskowski
authors.forename: Janet M
authors.initials: JM
authors.lastname: Thornton
mesh_terms: D001665:Binding Sites; D003198:Computer Simulation; D030562:Databases, Protein; D008956:Models, Chemical; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000032:analysis / Q000737:chemistry* / Q000145:classification / Q000378:metabolism*; D016415:Sequence Alignment / Q000379:methods; D020539:Sequence Analysis, Protein / Q000379:methods*; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins