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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao King's College, Lond...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1016/s0091-...
Part of book or chapter of book . 2007 . Peer-reviewed
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Analysis and Prediction of Mitochondrial Targeting Signals

Authors: Habib, Shukry; Neupert, Walter; Rapaport, Doron;

Analysis and Prediction of Mitochondrial Targeting Signals

Abstract

Publisher Summary This chapter describes the known mitochondrial-targeting signals, their analysis, and available methods to predict the presence of such signals in eukaryotic proteins. The best-characterized mitochondrial-targeting signal is the matrix-targeting signal—also called the presequence. Analysis of a large number of mitochondrial presequences suggested that most of them have the potential to form a positively charged amphiphilic α-helix in which segregation of positively charged and hydrophobic residues on opposite faces of the helix occurs. Two-dimensional nuclear magnetic resonance, fluorescence methods, and circular dichroism measurements demonstrated the ability of targeting sequences to form amphipathic α-helices in membranes or membrane-like environments, whereas in aqueous solution, they are essentially unstructured. The targeting of mitochondrial precursor proteins from the cytosol to the organelle and the subsequent intra-mitochondrial sorting depend on specific targeting and sorting information within the precursor sequence. In the case of the cleavable presequences, the characteristics of this signal are well understood and various bioinformatics and experimental tools are available to analyze them. The prediction provided by these programs is based mainly on physicochemical parameters, such as the abundance of certain amino acids and the hydrophobicity in certain regions, and/or analysis of the plain residue patterns in the amino acid sequences. Several bioinformatics tools, such as TargetP, PSORT II, MITOPRED, MitoProt II, and Predotar are also presented in the chapter.

Country
United Kingdom
Keywords

570, Protein, Post-Translational, Computational Biology, Protein Sorting Signals, Biological, 530, Models, Biological, Mitochondria, Mitochondrial Proteins, Protein Transport, Eukaryotic Cells, Models, Sequence Analysis, Protein, Mitochondrial Membranes, Animals, Humans, Sequence Analysis, Protein Processing, Post-Translational, Protein Processing, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
46
Top 10%
Top 10%
Top 10%
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