Bioinformatics Advance Access originally published online on February 26, 2004
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Bioinformatics 20(12) © Oxford University Press 2004; all rights reserved.
A knowledge-based scale for the analysis and prediction of buried and exposed faces of transmembrane domain proteins
1 Department of Physiology and Biophysics, Mount Sinai School of Medicine, New York, NY 10029, USA and 2 Department of Physiology and Biophysics, and Institute for Computational Biomedicine, Weill Medical College of Cornell University, New York, NY 10021, USA
Received on August 20, 2003; revised on January 10, 2004; accepted on January 11, 2004
Advance Access Publication February 26, 2004
Motivation: The dearth of structural data on 
-helical membrane proteins (MPs) has hampered thus far the development of reliable knowledge-based potentials that can be used for automatic prediction of transmembrane (TM) protein structure. While algorithms for identifying TM segments are available, modeling of the TM domains of -helical MPs involves assembling the segments into a bundle. This requires the correct assignment of the buried and lipid-exposed faces of the TM domains.
Results: A recent increase in the number of crystal structures of -helical MPs has enabled an analysis of the lipid-exposed surfaces and the interiors of such molecules on the basis of structure, rather than sequence alone. Together with a conservation criterion that is based on previous observations that conserved residues are mostly found in the interior of MPs, the bias of certain residue types to be preferably buried or exposed is proposed as a criterion for predicting the lipid-exposed and interior faces of TMs. Applications to known structures demonstrates 80% accuracy of this prediction algorithm.
Availability: The algorithm used for the predictions is implemented in the ProperTM Web server (http://icb.med.cornell.edu/services/propertm/start).
Contact: haw2002{at}med.cornell.edu
* To whom correspondence should be addressed.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  M. S. Taylor, H. K. Fung, R. Rajgaria, M. Filizola, H. Weinstein, and C. A. Floudas Mutations Affecting the Oligomerization Interface of G-Protein-Coupled Receptors Revealed by a Novel De Novo Protein Design Framework Biophys. J., April 1, 2008; 94(7): 2470 - 2481. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y. Park and V. Helms On the derivation of propensity scales for predicting exposed transmembrane residues of helical membrane proteins Bioinformatics, March 15, 2007; 23(6): 701 - 708. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. Beuming, L. Shi, J. A. Javitch, and H. Weinstein A Comprehensive Structure-Based Alignment of Prokaryotic and Eukaryotic Neurotransmitter/Na+ Symporters (NSS) Aids in the Use of the LeuT Structure to Probe NSS Structure and Function Mol. Pharmacol., November 1, 2006; 70(5): 1630 - 1642. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. Min, H. Wang, T.-T. Sun, and X.-P. Kong Structural basis for tetraspanin functions as revealed by the cryo-EM structure of uroplakin complexes at 6-A resolution J. Cell Biol., June 19, 2006; 173(6): 975 - 983. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. M. Cuthbertson, D. A. Doyle, and M. S.P. Sansom Transmembrane helix prediction: a comparative evaluation and analysis Protein Eng. Des. Sel., June 1, 2005; 18(6): 295 - 308. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. Beuming and H. Weinstein Modeling membrane proteins based on low-resolution electron microscopy maps: a template for the TM domains of the oxalate transporter OxlT Protein Eng. Des. Sel., March 1, 2005; 18(3): 119 - 125. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. J. Fleishman, S. Harrington, R. A. Friesner, B. Honig, and N. Ben-Tal An Automatic Method for Predicting Transmembrane Protein Structures Using Cryo-EM and Evolutionary Data Biophys. J., November 1, 2004; 87(5): 3448 - 3459. [Abstract] [Full Text] [PDF]
|
|