%0 Journal Article
%T SitesIdentify: a protein functional site prediction tool
%A Tracey Bray
%A Pedro Chan
%A Salim Bougouffa
%A Richard Greaves
%A Andrew J Doig
%A Jim Warwicker
%J BMC Bioinformatics
%D 2009
%I BioMed Central
%R 10.1186/1471-2105-10-379
%X Here we present a functional site prediction tool (SitesIdentify), based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites.SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/ webciteEfforts, primarily by structural genomics groups, have provided a rapidly growing number of protein structures with little or no functional annotation. This has caused new interest in the relationship between structure and function and has increased focus on ways to elucidate a protein's function from its structure rather than solely from sequence. In order to investigate the role of a protein using its structure, it is useful to be able to identify the portion of the protein that is most closely involved with its function. In the case of enzymes this is its active site, whilst non-enzymes have functionally important regions that are involved in ligand-binding or protein-protein interactions.There are currently several computational approaches that predict functional sites which use either structural or sequence information. The most widely used methods rely on sequence information in order to predict functionally important residues, due to the greater availability of sequence data as opposed to structural data for uncharacterised proteins. Sequence based methods mainly centre around the concept of functionally important residues being more highly conserved through evolution and identify the most conserved residues by comparing positions in a multiple seque
%U http://www.biomedcentral.com/1471-2105/10/379