Methods for the bioinformatic identification of bacterial lipoproteins encoded in the genomes of Gram-positive bacteria

  • Obaidur Rahman
  • Stephen P. Cummings
  • Dean J. Harrington
  • Iain C. SutcliffeEmail author


Bacterial lipoproteins are a diverse and functionally important group of proteins that are amenable to bioinformatic analyses because of their unique signal peptide features. Here we have used a dataset of sequences of experimentally verified lipoproteins of Gram-positive bacteria to refine our previously described lipoprotein recognition pattern (G+LPP). Sequenced bacterial genomes can be screened for putative lipoproteins using the G+LPP pattern. The sequences identified can then be validated using online tools for lipoprotein sequence identification. We have used our protein sequence datasets to evaluate six online tools for efficacy of lipoprotein sequence identification. Our analyses demonstrate that LipoP ( performs best individually but that a consensus approach, incorporating outputs from predictors of general signal peptide properties, is most informative.


Lipoproteins Signal peptides Bioinformatics Genomics Firmicutes Actinobacteria 



The authors thank Northumbria University for financial support from the ‘Research into Teaching’ programme.

Supplementary material

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Obaidur Rahman
    • 1
  • Stephen P. Cummings
    • 1
  • Dean J. Harrington
    • 2
  • Iain C. Sutcliffe
    • 1
    • 3
    Email author
  1. 1.Northumbria UniversityNewcastle upon TyneUK
  2. 2.University of BradfordWest YorkshireUK
  3. 3.Biomolecular and Biomedical Research Centre, School of Applied ScienceNorthumbria UniversityNewcastle upon TyneUK

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