Feature-based prediction of non-classical and leaderless protein secretion
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Feature-based prediction of non-classical and leaderless protein secretion. / Bendtsen, Jannick Dyrløv; Jensen, Lars Juhl; Blom, Nikolaj; Von Heijne, Gunnar; Brunak, Søren.
In: Protein Engineering Design and Selection (Print), Vol. 17, No. 4, 2004, p. 349-56.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Feature-based prediction of non-classical and leaderless protein secretion
AU - Bendtsen, Jannick Dyrløv
AU - Jensen, Lars Juhl
AU - Blom, Nikolaj
AU - Von Heijne, Gunnar
AU - Brunak, Søren
PY - 2004
Y1 - 2004
N2 - 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 https://www.cbs.dtu.dk/services/SecretomeP.
AB - 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 https://www.cbs.dtu.dk/services/SecretomeP.
U2 - 10.1093/protein/gzh037
DO - 10.1093/protein/gzh037
M3 - Journal article
C2 - 15115854
VL - 17
SP - 349
EP - 356
JO - Protein Engineering, Design and Selection
JF - Protein Engineering, Design and Selection
SN - 1741-0126
IS - 4
ER -
ID: 40740705