title: Structure-based function prediction: approaches and applications.
abstract: The ever increasing number of protein structures determined by structural genomic projects has spurred much interest in the development of methods for structure-based function prediction. Existing methods can be roughly classified in two groups: some use a comparative approach looking for the presence of structural motifs possibly associated with a known biochemical function. Other methods try to identify functional patches on the surface of a protein using only its physicochemical characteristics. This review will cover both kinds of approaches to structure-based function prediction as well as their use in real-world cases. The main issues and limitations in using protein structure to predict function will also be discussed. These are mainly: the assessment of the statistical significance of structural similarities and the extent to which these methods depend on the accuracy and availability of structural data.
authors.affiliation: Department of Biology, Centre for Molecular Bioinformatics, University of Tor Vergata, Rome, Italy. pier.federico.gherardini@uniroma2.it
authors.forename: Pier Federico
authors.initials: PF
authors.lastname: Gherardini
authors.forename: Manuela
authors.initials: M
authors.lastname: Helmer-Citterich
mesh_terms: D020816:Amino Acid Motifs; D030562:Databases, Protein; D008958:Models, Molecular; D011237:Predictive Value of Tests; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D016415:Sequence Alignment / Q000379:methods; D020539:Sequence Analysis, Protein / Q000379:methods; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins