Structure-based function prediction: approaches and applications.
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.
Gherardini
Pier Federico
PF
Department of Biology, Centre for Molecular Bioinformatics, University of Tor Vergata, Rome, Italy. pier.federico.gherardini@uniroma2.it
Helmer-Citterich
Manuela
M
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
D011506:Proteins