title: Membrane protein prediction methods.
abstract: We survey computational approaches that tackle membrane protein structure and function prediction. While describing the main ideas that have led to the development of the most relevant and novel methods, we also discuss pitfalls, provide practical hints and highlight the challenges that remain. The methods covered include: sequence alignment, motif search, functional residue identification, transmembrane segment and protein topology predictions, homology and ab initio modeling. In general, predictions of functional and structural features of membrane proteins are improving, although progress is hampered by the limited amount of high-resolution experimental information available. While predictions of transmembrane segments and protein topology rank among the most accurate methods in computational biology, more attention and effort will be required in the future to ameliorate database search, homology and ab initio modeling.
authors: Department of Biochemistry and Molecular Biophysics, Columbia University, 1130 St. Nicholas Ave., New York, NY 10032, USA.
authors: Marco
authors: M
authors: Punta
authors: Lucy R
authors: LR
authors: Forrest
authors: Henry
authors: H
authors: Bigelow
authors: Andrew
authors: A
authors: Kernytsky
authors: Jinfeng
authors: J
authors: Liu
authors: Burkhard
authors: B
authors: Rost
mesh_terms: D001671:Biochemistry / Q000379:methods*; D016208:Databases, Factual; D023281:Genomics; D008565:Membrane Proteins / Q000737:chemistry* / Q000235:genetics*; D008956:Models, Chemical; D011237:Predictive Value of Tests; D011487:Protein Conformation; D013329:Structure-Activity Relationship
chemical_list: D008565:Membrane Proteins