Literature DB >> 19153681

Online tools for predicting integral membrane proteins.

Henry Bigelow1, Burkhard Rost.   

Abstract

We identify and describe a set of tools readily available for integral membrane protein prediction. These tools address two problems: finding potential transmembrane proteins in a pool of new sequences, and identifying their transmembrane regions. All methods involve comparing the query protein against one or more target models. In the simplest of these, the target "model" is another protein sequence, while the more elaborate methods group together the entire set of t ansmembrane helical or transmembrane beta-barrel proteins. In general, prediction accuracy either in identifying new integral membrane proteins or transmembrane regions of known integral membrane proteins depends strongly on how closely the query fits the model. Because of this, the best approach is an opportunistic one: submit the protein of interest to all methods and choose the results with the highest confidence scores.

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Year:  2009        PMID: 19153681     DOI: 10.1007/978-1-60327-310-7_1

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  3 in total

1.  Structural genomics target selection for the New York consortium on membrane protein structure.

Authors:  Marco Punta; James Love; Samuel Handelman; John F Hunt; Lawrence Shapiro; Wayne A Hendrickson; Burkhard Rost
Journal:  J Struct Funct Genomics       Date:  2009-10-27

2.  Pattern of amino acid substitutions in transmembrane domains of β-barrel membrane proteins for detecting remote homologs in bacteria and mitochondria.

Authors:  David Jimenez-Morales; Jie Liang
Journal:  PLoS One       Date:  2011-11-01       Impact factor: 3.240

3.  Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences.

Authors:  Marcin J Mizianty; Lukasz Kurgan
Journal:  BMC Bioinformatics       Date:  2009-12-13       Impact factor: 3.169

  3 in total

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