Source:http://linkedlifedata.com/resource/pubmed/id/19585006
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Predicate | Object |
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rdf:type | |
lifeskim:mentions | |
pubmed:issue |
12
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pubmed:dateCreated |
2010-2-26
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pubmed:abstractText |
Integral membrane proteins display two major types of transmembrane structure, helical bundles and beta barrels. The main functional roles of transmembrane proteins are the transport of small molecules and cell signaling, and sometimes these two roles are coupled. For cytosolic, water-soluble proteins, signaling and regulatory functions are often carried out by intrinsically disordered regions. Our long range goal is to determine whether integral membrane proteins likewise use disordered regions for signaling and regulation. Here we carried out a systematic bioinformatics investigation of intrinsically disordered regions obtained from integral membrane proteins for which crystal structures have been determined, and for which the intrinsic disorder was identified as missing electron density. We found 120 disorder-containing integral membrane proteins having a total of 33675 residues, with 3209 of the residues distributed among 240 different disordered regions. These disordered regions were compared with those obtained from water-soluble proteins with regards to their amino acid compositional biases, and to the accuracies of various disorder predictors. The results of these analyses show that the disordered regions from helical bundle integral membrane proteins, those from beta barrel integral membrane proteins, and those from water soluble proteins all exhibit statistically distinct amino acid compositional biases. Despite these differences in composition, current algorithms make reasonably accurate predictions of disorder for these membrane proteins. Although the small size of the current data sets are limiting, these results suggest that developing new predictors that make use of data from disordered regions in helical bundles and beta barrels, especially as these datasets increase in size, will likely lead to significantly more accurate disorder predictions for these two classes of integral membrane proteins.
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pubmed:grant | |
pubmed:language |
eng
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pubmed:journal | |
pubmed:citationSubset |
IM
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pubmed:chemical | |
pubmed:status |
MEDLINE
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pubmed:month |
Dec
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pubmed:issn |
1742-2051
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pubmed:author | |
pubmed:issnType |
Electronic
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pubmed:volume |
5
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
1688-1702
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pubmed:dateRevised |
2011-3-3
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pubmed:meshHeading |
pubmed-meshheading:19585006-Amino Acid Sequence,
pubmed-meshheading:19585006-Bacterial Proteins,
pubmed-meshheading:19585006-Computational Biology,
pubmed-meshheading:19585006-Databases, Protein,
pubmed-meshheading:19585006-Humans,
pubmed-meshheading:19585006-Membrane Proteins,
pubmed-meshheading:19585006-Models, Molecular,
pubmed-meshheading:19585006-Protein Conformation,
pubmed-meshheading:19585006-ROC Curve,
pubmed-meshheading:19585006-Solubility
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pubmed:year |
2009
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pubmed:articleTitle |
Analysis of structured and intrinsically disordered regions of transmembrane proteins.
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pubmed:affiliation |
Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. binxue@iupui.edu
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pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't,
Research Support, N.I.H., Extramural
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