title: In silico methods for identifying organellar and suborganellar targeting peptides in Arabidopsis chloroplast proteins and for predicting the topology of membrane proteins.
abstract: Numerous experimental and in silico approaches have been developed for attempting to identify the -subcellular localisation of proteins. Approximately 2,000-4,000 proteins are thought to be targeted to plastids in plants, but a complete and unambiguous catalogue has yet to be drawn up. This article reviews the various prediction methods that identify plastid targeting sequences, and those that can help estimate location and topology within the plastid or plastid membranes. The most successful approaches are described in detail, with detailed notes to help avoid common pitfalls and advice on interpreting conflicting or ambiguous results. In most cases, it is best to try multiple approaches, and we also cover the powerful new integrated databases that provide a selected blend of experimental data and predictions.
authors.affiliation: Australian Research Council Centre of Excellence in Plant Energy Biology, University of Western Australia, Crawley, WA, Australia.
authors.forename: Sandra K
authors.initials: SK
authors.lastname: Tanz
authors.forename: Ian
authors.initials: I
authors.lastname: Small
mesh_terms: D017360:Arabidopsis / Q000378:metabolism*; D029681:Arabidopsis Proteins / Q000378:metabolism*; D060365:Chloroplast Proteins / Q000378:metabolism*; D002736:Chloroplasts / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods*; D008565:Membrane Proteins / Q000737:chemistry / Q000378:metabolism*; D010455:Peptides / Q000737:chemistry / Q000378:metabolism*; D021382:Protein Sorting Signals; D012984:Software; D013347:Subcellular Fractions / Q000378:metabolism
chemical_list: D029681:Arabidopsis Proteins; D060365:Chloroplast Proteins; D008565:Membrane Proteins; D010455:Peptides; D021382:Protein Sorting Signals