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Bioinformatics Advance Access published online on January 18, 2007
Bioinformatics, doi:10.1093/bioinformatics/btl653
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

On the derivation of propensity scales for predicting exposed transmembrane residues of helical membrane proteins

Yungki Park 1,* and Volkhard Helms 1

1Center for Bioinformatics, Saarland University, Germany.

*To whom correspondence should be addressed. Yungki Park, E-mail: yungki{at}bioinformatik.uni-saarland.de


  Abstract

Helical membrane proteins (HMPs) play a crucial role in diverse physiological processes. Given the difficulty in determining their structures by experimental techniques, it is desired to develop computational methods for predicting the burial status of transmembrane residues. Deriving a propensity scale for the 20 amino acids to be exposed to the lipid bilayer from known structures is central to developing such methods. A fundamental problem in this regard is what would be the optimal way of deriving propensity scales. Here, we show that this problem can be reformulated such that an optimal scale is straightforwardly obtained in an analytical fashion. The derived scale favorably compares with others in terms of both algorithmic optimality and practical prediction accuracy. It also allows interesting insights into the structural organization of HMPs. Furthermore, the presented approach can be applied to other bioinformatics problems of HMPs, too.

All the data sets and programs used in the study and detailed primary results are available upon request

Associate Editor: Anna Tramontano

Received on November 20, 2006; revised on December 20, 2006; accepted on December 21, 2006

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Y. Park and V. Helms
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[Abstract] [Full Text] [PDF]


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