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PEDS Advance Access originally published online on April 28, 2004
Protein Engineering Design and Selection 2004 17(4):349-356; doi:10.1093/protein/gzh037
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Protein Engineering, Design & Selection vol. 17 no. 4 © Oxford University Press 2004; all rights reserved

Feature-based prediction of non-classical and leaderless protein secretion

Jannick Dyrløv Bendtsen1, Lars Juhl Jensen1,2, Nikolaj Blom1, Gunnar von Heijne3 and Søren Brunak1,4

1Center for Biological Sequence Analysis BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark and 3Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden 2Present address: Computational Biology Unit, EMBL-Heidelberg, D-69117 Heidelberg and Max-Delbrück-Centre for Molecular Medicine, Robert-Rössle-Strasse 10, D-13092 Berlin, Germany

4 To whom correspondence should be addressed. E-mail: brunak{at}cbs.dtu.dk

We present a sequence-based method, SecretomeP, for the prediction of mammalian secretory proteins targeted to the non-classical secretory pathway, i.e. proteins without an N-terminal signal peptide. So far only a limited number of proteins have been shown experimentally to enter the non-classical secretory pathway. These are mainly fibroblast growth factors, interleukins and galectins found in the extracellular matrix. We have discovered that certain pathway-independent features are shared among secreted proteins. The method presented here is also capable of predicting (signal peptide-containing) secretory proteins where only the mature part of the protein has been annotated or cases where the signal peptide remains uncleaved. By scanning the entire human proteome we identified new proteins potentially undergoing non-classical secretion. Predictions can be made at http://www.cbs.dtu.dk/services/SecretomeP.

Received January 29, 2004; revised April 4, 2004; accepted April 6, 2004.

Edited by Andrej Sali


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