title: LigProf: a simple tool for in silico prediction of ligand-binding sites.
abstract: With the increasing amount of data provided by both high-throughput sequencing and structural genomics studies, there is a growing need for tools to augment functional predictions for protein sequences. Broad descriptions of function can be provided by establishing the presence of protein domains associated with a particular function. To extend the domain-based annotation, LigProf provides predictions of potential ligands that bind to a protein, as well as critical residues that stabilize ligands. A P-value statistic for estimating the significance of motif occurrence is provided for all sites. Although the usefulness of the method will rise with increasing numbers of crystallographically solved molecules deposited in the PDB database, we show that it can already be applied successfully to the highly represented ligand-bound protein kinase domains of viral and human origin. The LigProf webserver is freely available at: http://www.cropnet.pl/ligprof . At present, LigProf descriptors annotate and extend major protein families from the PfamA database.
authors.affiliation: Institute of Plant Genetics, Strzeszyńska 34, 60-479, Poznań, Poland. gkoc@igr.poznan.pl
authors.forename: Grzegorz
authors.initials: G
authors.lastname: Koczyk
authors.forename: Lucjan S
authors.initials: LS
authors.lastname: Wyrwicz
authors.forename: Leszek
authors.initials: L
authors.lastname: Rychlewski
mesh_terms: D001665:Binding Sites; D018360:Crystallography, X-Ray; D030562:Databases, Protein; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D014764:Viral Proteins / Q000737:chemistry / Q000378:metabolism
chemical_list: D008024:Ligands; D011506:Proteins; D014764:Viral Proteins