title: A Guide to Computational Methods for Predicting Mitochondrial Localization.
abstract: Predicting mitochondrial localization of proteins remains challenging for two main reasons: (1) Not only one but several mitochondrial localization signals exist, which primarily dictate the final destination of a protein in this organelle. However, most localization prediction algorithms rely on the presence of a so-called presequence (or N-terminal mitochondrial targeting peptide, mTP), which occurs in only ~70% of mitochondrial proteins. (2) The presequence is highly divergent on sequence level and therefore difficult to identify on the computer.In this chapter, we review a number of protein localization prediction programs and propose a strategy to predict mitochondrial localization. Finally, we give some helpful suggestions for bench scientists when working with mitochondrial protein candidates in silico.
authors.affiliation: Computational Biology Group, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152, Martinsried, Germany.
authors.forename: Su
authors.initials: S
authors.lastname: Sun
authors.affiliation: Computational Biology Group, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152, Martinsried, Germany. habermann@biochem.mpg.de.|Aix Marseille Université, CNRS, IBDM UMR 7288, 13288, Marseille, France. habermann@biochem.mpg.de.
authors.forename: Bianca H
authors.initials: BH
authors.lastname: Habermann
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D008928:Mitochondria / Q000378:metabolism*; D024101:Mitochondrial Proteins / Q000378:metabolism*; D021381:Protein Transport; D012984:Software; D064878:Web Browser
chemical_list: D024101:Mitochondrial Proteins
keywords: In silico; Mitochondrial protein localization; Mitochondrial targeting peptide; Prediction methods; Protein localization algorithms