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Hidden localization motifs: naturally occurring peroxisomal targeting signals in non-peroxisomal proteins

Georg Neuberger1, Markus Kunze2, Frank Eisenhaber1*, Johannes Berger2, Andreas Hartig3 and Cecile Brocard3

Author affiliations

1 Research Institute of Molecular Pathology (IMP), Dr Bohr-Gasse 7, A-1030 Vienna, Austria

2 Brain Research Institute, Department of Neuroimmunology, Medical University Vienna, Spitalgasse 4, A-1090 Vienna, Austria

3 Max F Perutz Laboratories, Institute of Biochemistry and Molecular Cell Biology, University of Vienna and Ludwig-Boltzmann-Forschungsstelle für Biochemie, Dr Bohr-Gasse 9, A-1030 Vienna, Austria

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Citation and License

Genome Biology 2004, 5:R97  doi:10.1186/gb-2004-5-12-r97

Published: 30 November 2004



Can sequence segments coding for subcellular targeting or for posttranslational modifications occur in proteins that are not substrates in either of these processes? Although considerable effort has been invested in achieving low false-positive prediction rates, even accurate sequence-analysis tools for the recognition of these motifs generate a small but noticeable number of protein hits that lack the appropriate biological context but cannot be rationalized as false positives.


We show that the carboxyl termini of a set of definitely non-peroxisomal proteins with predicted peroxisomal targeting signals interact with the peroxisomal matrix protein receptor peroxin 5 (PEX5) in a yeast two-hybrid test. Moreover, we show that examples of these proteins - chicken lysozyme, human tyrosinase and the yeast mitochondrial ribosomal protein L2 (encoded by MRP7) - are imported into peroxisomes in vivo if their original sorting signals are disguised. We also show that even prokaryotic proteins can contain peroxisomal targeting sequences.


Thus, functional localization signals can evolve in unrelated protein sequences as a result of neutral mutations, and subcellular targeting is hierarchically organized, with signal accessibility playing a decisive role. The occurrence of silent functional motifs in unrelated proteins is important for the development of sequence-based function prediction tools and the interpretation of their results. Silent functional signals have the potential to acquire importance in future evolutionary scenarios and in pathological conditions.