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Bioinformatics Advance Access published online on April 3, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn114
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© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Prediction of the translocon-mediated membrane insertion free energies of protein sequences

Yungki Park 1 and Volkhard Helms 1,*

1Center for Bioinformatics, Saarland University, Germany.

*To whom correspondence should be addressed. Volkhard Helms, E-mail: volkhard.helms{at}bioinformatik.uni-saarland.de


  Abstract

Motivation: Helical membrane proteins (HMPs) play crucial roles in a variety of cellular processes. Unlike water-soluble proteins, HMPs need not only to fold but also get inserted into the membrane to be fully functional. This process of membrane insertion is mediated by the translocon complex. Thus, it is of great interest to develop computational methods for predicting the translocon-mediated membrane insertion free energies of protein sequences.

Results: We have developed MINS (Membrane INSertion), a novel sequence-based computational method for predicting the membrane insertion free energies of protein sequences. A benchmark test gives a correlation coefficient of 0.74 between predicted and observed free energies for 357 known cases, which corresponds to a mean unsigned error of 0.41 kcal/mol. These results are significantly better than those obtained by traditional hydropathy analysis. Moreover, the ability of MINS to reasonably predict membrane insertion free energies of protein sequences allows for effective identification of TM segments. Subsequently, MINS was applied to predict the membrane insertion free energies of 316 TM segments found in known structures. An in-depth analysis of the predicted free energies reveals a number of interesting findings about the biogenesis and structural stability of HMPs.

Availability: A web server for MINS is available at http://service.bioinformatik.uni-saarland.de/mins.

Contact: volkhard.helms{at}bioinformatik.uni-saarland.de

Associate Editor: Prof. Anna Tramontano

Received on December 10, 2007; revised on March 4, 2008; accepted on March 29, 2008

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