title: Template-based prediction of protein function.
abstract: We discuss recent approaches for structure-based protein function annotation. We focus on template-based methods where the function of a query protein is deduced from that of a template for which both the structure and function are known. We describe the different ways of identifying a template. These are typically based on sequence analysis but new methods based on purely structural similarity are also being developed that allow function annotation based on structural relationships that cannot be recognized by sequence. The growing number of available structures of known function, improved homology modeling techniques and new developments in the use of structure allow template-based methods to be applied on a proteome-wide scale and in many different biological contexts. This progress significantly expands the range of applicability of structural information in function annotation to a level that previously was only achievable by sequence comparison.
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States. Electronic address: dsp18@columbia.edu.
authors: Donald
authors: D
authors: Petrey
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States.
authors: T Scott
authors: TS
authors: Chen
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States.
authors: Lei
authors: L
authors: Deng
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States.
authors: Jose Ignacio
authors: JI
authors: Garzon
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States.
authors: Howook
authors: H
authors: Hwang
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States.
authors: Gorka
authors: G
authors: Lasso
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States.
authors: Hunjoong
authors: H
authors: Lee
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States.
authors: Antonina
authors: A
authors: Silkov
authors: Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Department of Systems Biology, Center for Computational Biology and Bioinformatics, 1130 St. Nicholas Avenue, Room 815, New York, NY 10032, United States.
authors: Barry
authors: B
authors: Honig
mesh_terms: D000818:Animals; D006801:Humans; D000069550:Machine Learning; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D040681:Structural Homology, Protein
chemical_list: D011506:Proteins