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- Title
Combined prediction of Tat and Sec signal peptides with hidden Markov models.
- Authors
Bagos, Pantelis G; Nikolaou, Elisanthi P; Liakopoulos, Theodore D; Tsirigos, Konstantinos D
- Abstract
Computational prediction of signal peptides is of great importance in computational biology. In addition to the general secretory pathway (Sec), Bacteria, Archaea and chloroplasts possess another major pathway that utilizes the Twin-Arginine translocase (Tat), which recognizes longer and less hydrophobic signal peptides carrying a distinctive pattern of two consecutive Arginines (RR) in the n-region. A major functional differentiation between the Sec and Tat export pathways lies in the fact that the former translocates secreted proteins unfolded through a protein-conducting channel, whereas the latter translocates completely folded proteins using an unknown mechanism. The purpose of this work is to develop a novel method for predicting and discriminating Sec from Tat signal peptides at better accuracy.
- Publication
Bioinformatics (Oxford, England), 2010, Vol 26, Issue 22, p2811
- ISSN
1367-4811
- Publication type
Journal Article
- DOI
10.1093/bioinformatics/btq530