title: COFACTOR: an accurate comparative algorithm for structure-based protein function annotation.
abstract: We have developed a new COFACTOR webserver for automated structure-based protein function annotation. Starting from a structural model, given by either experimental determination or computational modeling, COFACTOR first identifies template proteins of similar folds and functional sites by threading the target structure through three representative template libraries that have known protein-ligand binding interactions, Enzyme Commission number or Gene Ontology terms. The biological function insights in these three aspects are then deduced from the functional templates, the confidence of which is evaluated by a scoring function that combines both global and local structural similarities. The algorithm has been extensively benchmarked by large-scale benchmarking tests and demonstrated significant advantages compared to traditional sequence-based methods. In the recent community-wide CASP9 experiment, COFACTOR was ranked as the best method for protein-ligand binding site predictions. The COFACTOR sever and the template libraries are freely available at http://zhanglab.ccmb.med.umich.edu/COFACTOR.
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI 48109-2218, USA.
authors.forename: Ambrish
authors.initials: A
authors.lastname: Roy
authors.forename: Jianyi
authors.initials: J
authors.lastname: Yang
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D004798:Enzymes / Q000737:chemistry / Q000502:physiology; D020407:Internet; D008024:Ligands; D058977:Molecular Sequence Annotation; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000235:genetics / Q000502:physiology*; D012984:Software
chemical_list: D004798:Enzymes; D008024:Ligands; D011506:Proteins