Prediction of beta-barrel membrane proteins by searching for restricted domains

Background: The identification of beta-barrel membrane proteins out
of a genomic/proteomic background is one of the rapidly developing
fields in bioinformatics. Our main goal is the prediction of such
proteins in genome/proteome wide analyses. Results: For the
prediction of beta-barrel membrane proteins within prokaryotic
proteomes a set of parameters was developed. We have focused on a
procedure with a low false positive rate beside a procedure with
lowest false prediction rate to obtain a high certainty for the
predicted sequences. We demonstrate that the discrimination between
beta-barrel membrane proteins and other proteins is improved by
analyzing a length limited region. The developed set of parameters
is applied to the proteome of E. coli and the results are compared
to four other described procedures. Conclusion: Analyzing the
beta-barrel membrane proteins revealed the presence of a defined
membrane inserted beta-barrel region. This information can now be
used to refine other prediction programs as well. So far, all
tested programs fail to predict outer membrane proteins in the
proteome of the prokaryote E. coli with high reliability. However,
the reliability of the prediction is improved significantly by a
combinatory approach of several programs. The consequences and
usability of the developed scores are discussed.