77
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Prediction of lipoprotein signal peptides in Gram-negative bacteria.

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          A method to predict lipoprotein signal peptides in Gram-negative Eubacteria, LipoP, has been developed. The hidden Markov model (HMM) was able to distinguish between lipoproteins (SPaseII-cleaved proteins), SPaseI-cleaved proteins, cytoplasmic proteins, and transmembrane proteins. This predictor was able to predict 96.8% of the lipoproteins correctly with only 0.3% false positives in a set of SPaseI-cleaved, cytoplasmic, and transmembrane proteins. The results obtained were significantly better than those of previously developed methods. Even though Gram-positive lipoprotein signal peptides differ from Gram-negatives, the HMM was able to identify 92.9% of the lipoproteins included in a Gram-positive test set. A genome search was carried out for 12 Gram-negative genomes and one Gram-positive genome. The results for Escherichia coli K12 were compared with new experimental data, and the predictions by the HMM agree well with the experimentally verified lipoproteins. A neural network-based predictor was developed for comparison, and it gave very similar results. LipoP is available as a Web server at www.cbs.dtu.dk/services/LipoP/.

          Related collections

          Author and article information

          Journal
          Protein Sci
          Protein science : a publication of the Protein Society
          Cold Spring Harbor Laboratory
          0961-8368
          0961-8368
          Aug 2003
          : 12
          : 8
          Affiliations
          [1 ] Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby 2800, Denmark.
          Article
          10.1110/ps.0303703
          2323952
          12876315
          128d299d-1234-4e5d-aedd-22cd4582bca6
          History

          Comments

          Comment on this article