Chapter title |
In Silico Tools for the Prediction of Protein Import into Secondary Plastids
|
---|---|
Chapter number | 25 |
Book title |
Plastids
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-8654-5_25 |
Pubmed ID | |
Book ISBNs |
978-1-4939-8653-8, 978-1-4939-8654-5
|
Authors |
Daniel Moog, Moog, Daniel |
Abstract |
The in silico identification of proteins targeting to secondary plastids is a difficult task. Such plastids are complex in structure and can be surrounded by up to four membranes, which have to be crossed during import. Nucleus-encoded plastidial preproteins in organisms with secondary plastids contain specific N-terminal targeting signals, the so-called bipartite targeting signal (BTS) sequences consisting of a classical signal peptide followed by a transit peptide-like sequence, mediating this intricate process. As these signal sequences differ significantly from transit peptides of plastid preproteins in plants and other organisms with primary plastids, existing in silico tools for primary plastid targeting prediction are not directly suitable to detect nucleus-encoded proteins destined for the import into secondary plastids. In this chapter I describe the current state-of-the-art methods to reliably predict proteins that might be imported into secondary plastids of red- and green-algal origin using either the "classical" approach, which involves a combination of bits of information produced by existing in silico tools, or, if available, via consulting specifically developed algorithms. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 4 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 2 | 50% |
Student > Bachelor | 1 | 25% |
Student > Ph. D. Student | 1 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 3 | 75% |
Engineering | 1 | 25% |