Skip to Main content Skip to Navigation
New interface
Journal articles

A Guide to Computational Methods for Predicting Mitochondrial Localization.

Su Sun Bianca Habermann 1, 2 
1 Computational Biology Group [Martinsried, Germany]
MPIB - Max-Planck-Institut für Biochemie = Max Planck Institute of Biochemistry
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.
Document type :
Journal articles
Complete list of metadata
Contributor : Bianca Habermann Connect in order to contact the contributor
Submitted on : Friday, September 14, 2018 - 2:36:40 PM
Last modification on : Thursday, September 1, 2022 - 9:02:10 AM




Su Sun, Bianca Habermann. A Guide to Computational Methods for Predicting Mitochondrial Localization.. Methods in Molecular Biology, 2018, pp.1-14. ⟨10.1007/978-1-4939-6824-4_1⟩. ⟨hal-01874603⟩



Record views