TY - JOUR
T1 - Locating proteins in the cell using TargetP, SignalP and related tools
AU - Emanuelsson, Olof
AU - Brunak, Søren
AU - von Heijne, Gunnar
AU - Nielsen, Henrik
PY - 2007
Y1 - 2007
N2 - Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.
AB - Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.
KW - Amino Acid Motifs
KW - Arabidopsis Proteins
KW - Computational Biology
KW - Protein Sorting Signals
KW - Proteins
KW - Sequence Analysis, Protein
KW - Software
U2 - 10.1038/nprot.2007.131
DO - 10.1038/nprot.2007.131
M3 - Journal article
C2 - 17446895
SN - 1750-2799
VL - 2
SP - 953
EP - 971
JO - Nature Protocols (Online)
JF - Nature Protocols (Online)
IS - 4
ER -