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TatP - 1.0

Presence and location of Twin-arginine signal peptides

TatP 1.0 server predicts the presence and location of Twin-arginine signal peptide cleavage sites in bacteria. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of two artificial neural networks. A postfiltering of the output based on regular expressions is possible.

NOTE: TatP is outdated and is only kept online for reference. Tat signal peptides are better predicted by the current version of SignalP!



Sequence submission: paste the sequence(s) and/or upload a local file

Paste a single sequence or several sequences in FASTA format into the field below:

Enter a regular expression:

Submit a file in FASTA format directly from your local disk:

No graphics
GIF (inline)
GIF (inline) and EPS (as links)

Output format
Short (no graphics!)

Truncate each sequence to max. residues.

We recommend that only the N-terminal part of each protein sequence is submitted.
Enter 0 (zero) to disable truncation.

At most 4,000 sequences and 2,000,000 amino acids per submission; each sequence not more than 5,000 amino acids.

The sequences are kept confidential and will be deleted after processing.


For publication of results, please cite:

  • Current version:

    Prediction of twin-arginine signal peptides.
    Jannick Dyrløv Bendtsen, Henrik Nielsen, David Widdick, Tracy Palmer and Søren Brunak.
    BMC bioinformatics 2005 6: 167.


1. Specify the input sequences

All the input sequences must be in one-letter amino acid code. The allowed alphabet (not case sensitive) is as follows:

A C D E F G H I K L M N P Q R S T V W Y and X (unknown)

All the alphabetic symbols not in the allowed alphabet will be converted to X before processing. All the non-alphabetic symbols, including white space and digits, will be ignored.

The sequences can be input in the following two ways:

  • Paste a single sequence (just the amino acids) or a number of sequences in FASTA format into the upper window of the main server page.

  • Select a FASTA file on your local disk, either by typing the file name into the lower window or by browsing the disk.

Both ways can be employed at the same time: all the specified sequences will be processed. However, there may be not more than 4,000 sequences and 2,000,000 amino acids in total in one submission. The sequences may not be longer than 5,000 amino acids.

2. Customize your run

  • Regular expressions:
    In this field you can enter your own regular expression for filtering. A default expession is presented in the field.
    The default regular expression 'RR.[FGAVML][LITMVF]' means arginines in the two first positions, any amino acid in the third position, (F or G or A or V or M or L) in the forth position and finally any of the following amino acids in the fifth position (L or I or T or M or V or F).
    Character Name Meaning
    . dot Any amino acid is allowed
    [...] character class Amino acids listed between the brackets are allowed
    [^...] negated character class Amino acids listed between the brackets and the ^ are not allowed

  • Graphics output:
    No graphics, in line GIF or in line GIF and EPS as links. See the Output format for examples.

  • Text output:
    Standard, full or short output format. See the Output format for examples.

  • Sequence truncation:
    Signal peptides occurr at the N-terminal end of protein sequences; they are seldom longer than 45 amino acids. It is normally not meaningful to submit more than 60-70 amino acids per sequence. Therefore, the default truncation has been set to 70.

3. Submit the job

Click on the "Submit" button. The status of your job (either 'queued' or 'running') will be displayed and constantly updated until it terminates and the server output appears in the browser window.

At any time during the wait you may enter your e-mail address and simply leave the window. Your job will continue; you will be notified by e-mail when it has terminated. The e-mail message will contain the URL under which the results are stored; they will remain on the server for 24 hours for you to collect them.

Output format

Description of the scores
Examples of standard output
Examples of short output


The scores and graphical output is almost identical to the output of the SignalP server. The presented scores are calculated in the same way as for SignalP.

The graphical output from TatP (neural network) comprises three different scores, C, S and Y. Two additional scores are reported in the SignalP3-NN output, namely the S-mean and the D-score, but these are only reported as numerical values.

For each prediction, two different neural networks are used, one for predicting the actual signal peptide and one for predicting the position of the signal peptidase I (SPase I) cleavage site. The S-score for the signal peptide prediction is reported for every single amino acid position in the submitted sequence, with high scores indicating that the corresponding amino acid is part of a signal peptide, and low scores indicating that the amino acid is part of a mature protein.

The C-score is the ``cleavage site'' score. For each position in the submitted sequence, a C-score is reported, which should only be significantly high at the cleavage site. Confusion is often seen with the position numbering of the cleavage site. When a cleavage site position is referred to by a single number, the number indicates the first residue in the mature protein, meaning that a reported cleavage site between amino acid 26-27 corresponds to that the mature protein starts at (and include) position 27.

Y-max is a derivative of the C-score combined with the S-score resulting in a better cleavage site prediction than the raw C-score alone. This is due to the fact that multiple high-peaking C-scores can be found in one sequence, where only one is the true cleavage site. The cleavage site is assigned from the Y-score where the slope of the S-score is steep and a significant C-score is found.

The S-mean is the average of the S-score, ranging from the N-terminal amino acid to the amino acid assigned with the highest Y-max score, thus the S-mean score is calculated for the length of the predicted signal peptide.

The D-score is introduced in SignalP version 3.0 and is a simple average of the S-mean and Y-max score. The score shows superior discrimination performance of secretory and non-secretory proteins to that of the S-mean score which was used in SignalP version 1 and 2. In TatP the D-score is used for final discrimination of secretory vs. non-secretory.

For non-secretory proteins all the scores represented in the TatP-NN output should ideally be very low.


By default the server produces the following output for each input sequence:

Example 1: Secretory protein with Tat signal peptide

The example below shows the output for Membrane-bound hydrogenase 1 small subunit, taken from the
Swiss-Prot entry MBHS_ECOLI. The signal peptide prediction is consistent with the database annotation.


TatP-NN result:

# data

>MBHS_ECOLI            length = 70
# Measure  Position  Value  Cutoff  signal peptide?
  max. C    46       0.831   0.48   YES
  max. Y    46       0.826   0.41   YES
  max. S    34       0.923   0.84   YES
  mean S     1-45    0.804   0.46   YES
  max. D     1-45    0.815   0.44   YES
# Most likely cleavage site between pos. 45 and 46: AWA-LE
# Found RRQGV as Tat motif starting at position 12 
Used regex: RR.[FGAVML][LITMVF]


When selecting the short output format, the prediction for each submitted sequence (in a multisequence FASTA file) are reported in a condensed text form without any graphical output. All entries are separated by a "//". The following example show one positive and one negative prediction. The regular expression entered on the webpage is also presented in the output.
>MBHS_ECOLI            length = 70
# Measure  Position  Value  Cutoff  signal peptide?
  max. C    46       0.831   0.48   YES
  max. Y    46       0.826   0.41   YES
  max. S    34       0.923   0.84   YES
  mean S     1-45    0.804   0.46   YES
  max. D     1-45    0.815   0.44   YES
# Most likely cleavage site between pos. 45 and 46: AWA-LE
# Found RRQGV as Tat motif starting at position 12 
Used regex: RR.[FGAVML][LITMVF]
>AAT_THEMA             length = 70
# Measure  Position  Value  Cutoff  signal peptide?
  max. C    22       0.279   0.48   NO
  max. Y    22       0.090   0.41   NO
  max. S     6       0.102   0.84   NO
  mean S     1-21    0.057   0.46   NO
  max. D     1-21    0.073   0.44   NO
Used regex: RR.[FGAVML][LITMVF]


Original method (TatP v. 1.0)

Prediction of twin-arginine signal peptides
Jannick Dyrløv Bendtsen, Henrik Nielsen, David Widdick, Tracy Palmer and Søren Brunak
BMC bioinformatics 2005 6: 167.

Abstract Background:
Proteins carrying twin-arginine (Tat) signal peptides are exported into the periplasmic compartment or extracellular environment independently of the classical Sec-dependent 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.
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.
The method developed here is able to discriminate Tat signal peptides from cytoplasmic proteins carrying a similar motif, as well as from Sec signal peptides, with high accuracy. The method allows filtering of input sequences based on Perl syntax regular expressions, whereas hydrophobicity discrimination of Tat- and Sec-signal peptides is carried out by an artificial neural network. A potential cleavage site of the predicted Tat signal peptide is also reported.

PMID: 15992409         doi:10.1186/1471-2105-6-167

Scientific Background

For a brief description of the TatP prediction method please consult the article abstracts.

Biological background

Upon public release of this method, more information will be added to this site.

Recently published papers regarding twin-arginine translocation can be found by quering PubMed.


A curated set of E. coli Tat signal peptides can be found at this website hosted by Tracy Palmer. E. coli dataset

Positive training set in fasta format Download
Negative training set in fasta format Download

Negative test set (cytoplasmic RR) Download Output
Negative test set (transmem RR) Download Output

Software Downloads


If you need help regarding technical issues (e.g. errors or missing results) contact Technical Support. Please include the name of the service and version (e.g. NetPhos-4.0). If the error occurs after the job has started running, please include the JOB ID (the long code that you see while the job is running).

If you have scientific questions (e.g. how the method works or how to interpret results), contact Correspondence.

Correspondence: Technical Support: