Prediction of twin-arginine signal peptides

Background: Proteins carrying twin-arginine (Tat) signal peptides are exported into the periplasmic compartment or extracellular environment independently of the classical Secdependent translocation pathway. To complement other methods for classical signal peptide prediction we here present a publicly available method, TatP, for prediction of bacterial Tat signal peptides. Results: We have retrieved sequence data for Tat substrates in order to train a computational method for discrimination of Sec and Tat signal peptides. The TatP method is able to positively classify 91% of 35 known Tat signal peptides and 84% of the annotated cleavage sites of these Tat signal peptides were correctly predicted. This method generates far less false positive predictions on various datasets than using simple pattern matching. Moreover, on the same datasets TatP generates less false positive predictions than a complementary rule based prediction method. Conclusion: The method developed here is able to d...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Jannick Dyrløv Bendtsen, Henrik Nielsen, David Widdick, Tracy Palmer, Søren Brunak
• Keywords: BMCBI 2005, Peptide, Signal Peptide, Tat Signal