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      Investigation of transmembrane proteins using a computational approach

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      1 , 2 , 3 , 4 , , 1 ,
      BMC Genomics
      BioMed Central
      The 2007 International Conference on Bioinformatics & Computational Biology (BIOCOMP'07)
      25–28 June 2007

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          Abstract

          Background

          An important subfamily of membrane proteins are the transmembrane α-helical proteins, in which the membrane-spanning regions are made up of α-helices. Given the obvious biological and medical significance of these proteins, it is of tremendous practical importance to identify the location of transmembrane segments. The difficulty of inferring the secondary or tertiary structure of transmembrane proteins using experimental techniques has led to a surge of interest in applying techniques from machine learning and bioinformatics to infer secondary structure from primary structure in these proteins. We are therefore interested in determining which physicochemical properties are most useful for discriminating transmembrane segments from non-transmembrane segments in transmembrane proteins, and for discriminating intrinsically unstructured segments from intrinsically structured segments in transmembrane proteins, and in using the results of these investigations to develop classifiers to identify transmembrane segments in transmembrane proteins.

          Results

          We determined that the most useful properties for discriminating transmembrane segments from non-transmembrane segments and for discriminating intrinsically unstructured segments from intrinsically structured segments in transmembrane proteins were hydropathy, polarity, and flexibility, and used the results of this analysis to construct classifiers to discriminate transmembrane segments from non-transmembrane segments using four classification techniques: two variants of the Self-Organizing Global Ranking algorithm, a decision tree algorithm, and a support vector machine algorithm. All four techniques exhibited good performance, with out-of-sample accuracies of approximately 75%.

          Conclusions

          Several interesting observations emerged from our study: intrinsically unstructured segments and transmembrane segments tend to have opposite properties; transmembrane proteins appear to be much richer in intrinsically unstructured segments than other proteins; and, in approximately 70% of transmembrane proteins that contain intrinsically unstructured segments, the intrinsically unstructured segments are close to transmembrane segments.

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          Most cited references37

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          Analysis of membrane and surface protein sequences with the hydrophobic moment plot.

          An algorithm has been developed which identifies alpha-helices involved in the interactions of membrane proteins with lipid bilayers and which distinguishes them from helices in soluble proteins. The membrane-associated helices are then classified with the aid of the hydrophobic moment plot, on which the hydrophobic moment of each helix is plotted as a function of its hydrophobicity. The magnitude of hydrophobic moment measures the amphiphilicity of the helix (and hence its tendency to seek a surface between hydrophobic and hydrophilic phases), and the hydrophobicity measures its affinity for the membrane interior. Segments of membrane proteins in alpha-helices tend to fall in one of three regions of a hydrophobic moment plot: (1) monomeric transmembrane anchors (class I HLA transmembrane sequences) lie in the region of highest hydrophobicity and smallest hydrophobic moment; (2) helices presumed to be paired (such as the transmembrane M segments of surface immunoglobulins) and helices which are bundled together in membranes (such as bacteriorhodopsin) fall in the adjacent region with higher hydrophobic moment and smaller hydrophobicity; and (3) helices from surface-seeking proteins (such as melittin) fall in the region with still higher hydrophobic moment. alpha-Helices from globular proteins mainly fall in a region of lower mean hydrophobicity and hydrophobic moment. Application of these methods to the sequence of diphtheria toxin suggests four transmembrane helices and a surface-seeking helix in fragment B, the moiety known to have transmembrane function.
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            • Record: found
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            The protein trinity--linking function and disorder.

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              • Record: found
              • Abstract: not found
              • Article: not found

              Identifying nonpolar transbilayer helices in amino acid sequences of membrane proteins.

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                Author and article information

                Conference
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2008
                20 March 2008
                : 9
                : Suppl 1
                : S7
                Affiliations
                [1 ]Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
                [2 ]National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
                [3 ]Center for Computational Biology and Bioinformatics, Indiana University Schools of Medicine and Informatics, 410 W. 10th Street, Indianapolis, IN 46202, USA
                [4 ]Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, 39406, USA
                Article
                1471-2164-9-S1-S7
                10.1186/1471-2164-9-S1-S7
                2386072
                18366620
                9906d4cd-37a0-4e3e-af47-71598e5dd775
                Copyright © 2008 Yang et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                The 2007 International Conference on Bioinformatics & Computational Biology (BIOCOMP'07)
                Las Vegas, NV, USA
                25–28 June 2007
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                Research

                Genetics
                Genetics

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