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The Signal Peptide Prediction plugin can be used to find secretory signal peptides in protein sequences.

When the plugin is installed, you will find it in the Toolbox under Protein Analyses.

Signal peptides target proteins to the extracellular environment either through direct plasmamembrane translocation in prokaryotes or are routed through the endoplasmatic reticulum in eukaryotic cells. The signal peptide is removed from the resulting mature protein during translocation across the membrane.

For prediction of signal peptides, we query SignalP-NN [Nielsen et al., 1997] [Bendtsen et al., 2004a] located at www.cbs.dtu.dk/services/SignalP.

An active internet connection is required to run the signal peptide prediction. Predicted signal peptides can automatically be added to the sequence as annotations or predictions can be viewed in text.

In order to predict potential signal peptides of proteins, the D-score from the SignalP output is used for discrimination of signal peptide versus non-signal peptide. This score has been shown to be the most accurate [Klee and Ellis, 2005] in an evaluation study of signal peptide predictors.

These organisms can be selected:

  • Eukaryote
  • Gram-negative bacteria
  • Gram-positive bacteria

The predictions obtained can either be shown as annotations on the sequence or be shown as the detailed, full text output from the SignalP method. This can be used to interpret borderline predictions.

You can perform the analysis on several protein sequences at a time. This will add annotations to all the sequences and open a view for each sequence if a signal peptide is found.

After running the prediction as described above, the protein sequence will show predicted signal peptides as annotations on the original sequence.

Each annotation will carry a tooltip note saying that the corresponding annotation is predicted with SignalP version 3.0. Additional notes can be added, and undesired annotations can be removed through the edit annotation feature.

Additional information on SignalP and Center for Biological Sequence analysis (CBS) can be found at http://www.cbs.dtu.dk and in the original research paper [Nielsen et al., 1997] [Bendtsen et al., 2004a].



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