PRED-TAT

PRED-TAT predicts and discriminates signal peptides for the Sec and Tat (Twin-Arginine translocase) pathways and identifies their signal peptide cleavage sites.

Key Features:

• Discrimination Capability: Distinguishes Sec (general secretory pathway) and Tat (Twin-Arginine translocase) signal peptides to assign pathway targeting.
• Cleavage Site Prediction: Predicts the cleavage sites of signal peptides.
• Hidden Markov Models: Employs Hidden Markov Models (HMMs) within a modular architecture tailored to Sec and Tat signal peptides.
• Performance: Validated on experimentally verified datasets, showing superior performance to TatP and TATFIND for Tat signal peptides and competitive performance with SignalP and Phobius for Sec signal peptides.

Scientific Applications:

• Protein Engineering: Assists design of proteins with desired secretion characteristics by predicting pathway targeting and cleavage sites.
• Microbial Biotechnology: Informs optimization of microbial production systems through understanding of protein export and targeting.
• Basic Research: Supports studies of protein translocation mechanisms in Bacteria, Archaea, and chloroplasts.

Methodology:

Uses Hidden Markov Models (HMMs) within a modular architecture tailored for Sec and Tat signal peptides.