ProP - 1.0

Arginine and lysine propeptide cleavage sites in eukaryotic protein sequences

The ProP 1.0 server predicts arginine and lysine propeptide cleavage sites in eukaryotic protein sequences using an ensemble of neural networks. Furin-specific prediction is the default. It is also possible to perform a general proprotein convertase (PC) prediction.

For convenience, this server is integrated with the SignalP-3.0 server predicting the presence and location of signal peptide cleavage sites.


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:

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

Generate graphics Include signal peptide prediction
Verbose output General PC prediction

At most 2000 sequences and 200,000 amino acids per submission; each sequence not more than 4,000 amino acids.

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


For publication of results, please cite:

Prediction of proprotein convertase cleavage sites.
Peter Duckert, Søren Brunak and Nikolaj Blom.
Protein Engineering, Design and Selection: 17: 107-112, 2004.


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 other symbols will be converted to X before processing. 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 2,000 sequences and 200,000 amino acids in total in one submission. The sequences may not be longer than 4,000 amino acids.

2. Customize your run

  • By default the server produces graphical output illustrating the predictions. You can suppress that by un-checking the button labelled 'Generate graphics'.

  • Prediction of the presence and location of signal peptide cleavage sites by the SignalP server is included by default. You can suppress that by un-checking the button labelled 'Include signal peptide prediction'.

  • Check the button labelled 'Verbose output' to display the scores produced by the 4 individual neural networks alongside the average score. The default is to show the average score only.

  • The server performs Furin-specific propeptide cleavage site prediction by default. Check the button labelled 'General PC prediction' to perform that prediction instead.

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


For each input sequence the following is shown (see the example below):
  • Header line, quoting the name and length of the sequence.

  • Sequence, in one-letter code, as it was interpreted by the server.

  • Annotation overview, showing the predictions residue by residue, as follows:

    . (dot) neutral place-holder
    s predicted to be within a signal peptide
    P predicted to be followed by a propeptide cleavage site

  • Prediction score table, quoting the position, context and score for each arginine (R) and lysine (K) residue in the sequence.

    If the score is >0.5 the residue is predicted to be followed by a propeptide cleavage site; the higher the score the more confident the prediction.

  • Graph, in GIF, illustrating the predictions.

    For each arginine (R) and lysine (K) the prediction score is plotted against the position in the sequence. If a signal peptide cleavage site has been predicted it is also shown in the graph.

The example below shows the output for glial cell line-derived neurotrophic factor precursor (ATF-1), taken from the Swiss-Prot entry GDNF_HUMAN. The signal peptide prediction is consistent with the database annotation. Two propeptide cleavage sites are predicted; one of them (pos. 77-78) is annotated in the database. The other prediction (pos. 168-169) is false.


         ##### ProP v.1.0b ProPeptide Cleavage Site Prediction #####

         ##### Furin-type cleavage site prediction (Arginine/Lysine residues) #####

  211 GDNF_HUMAN  
sssssssssssssssssss.........................................................P...      80
................................................................................     160
.......P...........................................                                  240
Signal peptide cleavage site predicted:	between pos. 19 and 20: ASA-FP
Propeptide cleavage sites predicted:	Arg(R)/Lys(K): 2

Name           Pos    Context     Score  Pred
GDNF_HUMAN       2    -----MK|LW  0.069    .
GDNF_HUMAN      26    FPLPAGK|RP  0.054    .
GDNF_HUMAN      27    PLPAGKR|PP  0.120    .
GDNF_HUMAN      36    EAPAEDR|SL  0.134    .
GDNF_HUMAN      40    EDRSLGR|RR  0.074    .
GDNF_HUMAN      41    DRSLGRR|RA  0.163    .
GDNF_HUMAN      42    RSLGRRR|AP  0.124    .
GDNF_HUMAN      73    FIQATIK|RL  0.059    .
GDNF_HUMAN      74    IQATIKR|LK  0.140    .
GDNF_HUMAN      76    ATIKRLK|RS  0.062    .
GDNF_HUMAN      77    TIKRLKR|SP  0.802 *ProP*
GDNF_HUMAN      81    LKRSPDK|QM  0.062    .
GDNF_HUMAN      88    QMAVLPR|RE  0.090    .
GDNF_HUMAN      89    MAVLPRR|ER  0.108    .
GDNF_HUMAN      91    VLPRRER|NR  0.146    .
GDNF_HUMAN      93    PRRERNR|QA  0.152    .
GDNF_HUMAN     104    ANPENSR|GK  0.088    .
GDNF_HUMAN     106    PENSRGK|GR  0.071    .
GDNF_HUMAN     108    NSRGKGR|RG  0.099    .
GDNF_HUMAN     109    SRGKGRR|GQ  0.254    .
GDNF_HUMAN     112    KGRRGQR|GK  0.251    .
GDNF_HUMAN     114    RRGQRGK|NR  0.091    .
GDNF_HUMAN     116    GQRGKNR|GC  0.095    .
GDNF_HUMAN     137    GLGYETK|EE  0.058    .
GDNF_HUMAN     143    KEELIFR|YC  0.112    .
GDNF_HUMAN     158    AETTYDK|IL  0.054    .
GDNF_HUMAN     161    TYDKILK|NL  0.067    .
GDNF_HUMAN     165    ILKNLSR|NR  0.072    .
GDNF_HUMAN     167    KNLSRNR|RL  0.070    .
GDNF_HUMAN     168    NLSRNRR|LV  0.767 *ProP*
GDNF_HUMAN     173    RRLVSDK|VG  0.064    .
GDNF_HUMAN     180    VGQACCR|PI  0.080    .
GDNF_HUMAN     201    LVYHILR|KH  0.093    .
GDNF_HUMAN     202    VYHILRK|HS  0.074    .
GDNF_HUMAN     206    LRKHSAK|RC  0.095    .
GDNF_HUMAN     207    RKHSAKR|CG  0.222    .


Prediction of proprotein convertase cleavage sites.
Peter Duckert, Søren Brunak and Nikolaj Blom1.
Protein Engineering, Design and Selection: 17: 107-112, 2004.

1to whom correspondence should be addressed, e-mail:

Center for Biological Sequence Analysis, BioCentrum-DTU, The Technical University of Denmark, DK-2800 Lyngby, Denmark


Many secretory proteins and peptides are synthesized as inactive precursors that in addition to signal peptide cleavage undergo post-translational processing to become biologically active polypeptides. Precursors are usually cleaved at sites composed of single or paired basic amino acid residues by members of the subtilisin/kexin-like proprotein convertase (PC) family. In mammals, seven members have been identified, with furin being the one first discovered and best characterized. Recently, the involvement of furin in diseases ranging from Alzheimer's disease and cancer to anthrax and Ebola fever has created additional focus on proprotein processing. We have developed a method for prediction of cleavage sites for PCs based on artificial neural networks. Two different types of neural networks have been constructed: a furin-specific network based on experimental results derived from the literature, and a general PC-specific network trained on data from the Swiss-Prot protein database. The method predicts cleavage sites in independent sequences with a sensitivity of 95% for the furin neural network and 62% for the general PC network.

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