Flavors of protein disorder
Intrinsically disordered proteins are characterized by long regions lacking 3‐D structure in their native states, yet they have been so far associated with 28 distinguishable functions. Previous studies showed that protein predictors trained on disorder from one type of protein often achieve poor ac...
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Veröffentlicht in: | Proteins, structure, function, and bioinformatics structure, function, and bioinformatics, 2003-09, Vol.52 (4), p.573-584 |
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description | Intrinsically disordered proteins are characterized by long regions lacking 3‐D structure in their native states, yet they have been so far associated with 28 distinguishable functions. Previous studies showed that protein predictors trained on disorder from one type of protein often achieve poor accuracy on disorder of proteins of a different type, thus indicating significant differences in sequence properties among disordered proteins. Important biological problems are identifying different types, or flavors, of disorder and examining their relationships with protein function. Innovative use of computational methods is needed in addressing these problems due to relative scarcity of experimental data and background knowledge related to protein disorder. We developed an algorithm that partitions protein disorder into flavors based on competition among increasing numbers of predictors, with prediction accuracy determining both the number of distinct predictors and the partitioning of the individual proteins. Using 145 variously characterized proteins with long (>30 amino acids) disordered regions, 3 flavors, called V, C, and S, were identified by this approach, with the V subset containing 52 segments and 7743 residues, C containing 39 segments and 3402 residues, and S containing 54 segments and 5752 residues. The V, C, and S flavors were distinguishable by amino acid compositions, sequence locations, and biological function. For the sequences in SwissProt and 28 genomes, their protein functions exhibit correlations with the commonness and usage of different disorder flavors, suggesting different flavor‐function sets across these protein groups. Overall, the results herein support the flavor‐function approach as a useful complement to structural genomics as a means for automatically assigning possible functions to sequences. Proteins 2003;52:573–584. © 2003 Wiley‐Liss, Inc. |
doi_str_mv | 10.1002/prot.10437 |
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Keith ; Obradovic, Zoran</creator><creatorcontrib>Vucetic, Slobodan ; Brown, Celeste J. ; Dunker, A. Keith ; Obradovic, Zoran</creatorcontrib><description>Intrinsically disordered proteins are characterized by long regions lacking 3‐D structure in their native states, yet they have been so far associated with 28 distinguishable functions. Previous studies showed that protein predictors trained on disorder from one type of protein often achieve poor accuracy on disorder of proteins of a different type, thus indicating significant differences in sequence properties among disordered proteins. Important biological problems are identifying different types, or flavors, of disorder and examining their relationships with protein function. Innovative use of computational methods is needed in addressing these problems due to relative scarcity of experimental data and background knowledge related to protein disorder. We developed an algorithm that partitions protein disorder into flavors based on competition among increasing numbers of predictors, with prediction accuracy determining both the number of distinct predictors and the partitioning of the individual proteins. Using 145 variously characterized proteins with long (>30 amino acids) disordered regions, 3 flavors, called V, C, and S, were identified by this approach, with the V subset containing 52 segments and 7743 residues, C containing 39 segments and 3402 residues, and S containing 54 segments and 5752 residues. The V, C, and S flavors were distinguishable by amino acid compositions, sequence locations, and biological function. For the sequences in SwissProt and 28 genomes, their protein functions exhibit correlations with the commonness and usage of different disorder flavors, suggesting different flavor‐function sets across these protein groups. Overall, the results herein support the flavor‐function approach as a useful complement to structural genomics as a means for automatically assigning possible functions to sequences. 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Keith</creatorcontrib><creatorcontrib>Obradovic, Zoran</creatorcontrib><title>Flavors of protein disorder</title><title>Proteins, structure, function, and bioinformatics</title><addtitle>Proteins</addtitle><description>Intrinsically disordered proteins are characterized by long regions lacking 3‐D structure in their native states, yet they have been so far associated with 28 distinguishable functions. Previous studies showed that protein predictors trained on disorder from one type of protein often achieve poor accuracy on disorder of proteins of a different type, thus indicating significant differences in sequence properties among disordered proteins. Important biological problems are identifying different types, or flavors, of disorder and examining their relationships with protein function. Innovative use of computational methods is needed in addressing these problems due to relative scarcity of experimental data and background knowledge related to protein disorder. We developed an algorithm that partitions protein disorder into flavors based on competition among increasing numbers of predictors, with prediction accuracy determining both the number of distinct predictors and the partitioning of the individual proteins. Using 145 variously characterized proteins with long (>30 amino acids) disordered regions, 3 flavors, called V, C, and S, were identified by this approach, with the V subset containing 52 segments and 7743 residues, C containing 39 segments and 3402 residues, and S containing 54 segments and 5752 residues. The V, C, and S flavors were distinguishable by amino acid compositions, sequence locations, and biological function. For the sequences in SwissProt and 28 genomes, their protein functions exhibit correlations with the commonness and usage of different disorder flavors, suggesting different flavor‐function sets across these protein groups. Overall, the results herein support the flavor‐function approach as a useful complement to structural genomics as a means for automatically assigning possible functions to sequences. Proteins 2003;52:573–584. © 2003 Wiley‐Liss, Inc.</description><subject>Algorithms</subject><subject>Archaeal Proteins - chemistry</subject><subject>Bacterial Proteins - chemistry</subject><subject>Computational Biology - methods</subject><subject>Databases, Protein</subject><subject>Drosophila Proteins - chemistry</subject><subject>Fungal Proteins - chemistry</subject><subject>genomics</subject><subject>Helminth Proteins - chemistry</subject><subject>Plant Proteins - chemistry</subject><subject>Protein Conformation</subject><subject>Protein Folding</subject><subject>Protein Structure, Secondary</subject><subject>Proteins - chemistry</subject><subject>Reproducibility of Results</subject><subject>secondary structure</subject><subject>sequence composition</subject><subject>signaling and regulatory proteins</subject><subject>structure prediction</subject><subject>unfolded proteins</subject><issn>0887-3585</issn><issn>1097-0134</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEFPAjEQRhujEUQvXk0MJw8mq9Ntu22PSgRNiCDB6K3ptt1kdWGxBZV_b3FRb55mDm_ezDcIHWO4wADp5cLXy9hRwndQG4PkCWBCd1EbhOAJYYK10EEILwCQSZLtoxZOZeQZb6OTfqXfax-6ddHdeFw579oy1N46f4j2Cl0Fd7StHfTYv5n2bpPhaHDXuxomhqZxWVzCRSqsZFgaTiWxxFHg2lqgNHU5x0QXnFGthcaSWlsYJyBn2uQiNZkgHXTWeOMBbysXlmpWBuOqSs9dvQqKE0Y4jZoOOm9A4-sQvCvUwpcz7dcKg9q8Qm0iqO9XRPh0a13lM2f_0G32COAG-Cgrt_5HpcaT0fRHmjQzZVi6z98Z7V9Vxgln6ul-oLLr50n_4Z6pMfkCqeV26Q</recordid><startdate>200309</startdate><enddate>200309</enddate><creator>Vucetic, Slobodan</creator><creator>Brown, Celeste J.</creator><creator>Dunker, A. 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Keith</au><au>Obradovic, Zoran</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Flavors of protein disorder</atitle><jtitle>Proteins, structure, function, and bioinformatics</jtitle><addtitle>Proteins</addtitle><date>2003-09</date><risdate>2003</risdate><volume>52</volume><issue>4</issue><spage>573</spage><epage>584</epage><pages>573-584</pages><issn>0887-3585</issn><eissn>1097-0134</eissn><abstract>Intrinsically disordered proteins are characterized by long regions lacking 3‐D structure in their native states, yet they have been so far associated with 28 distinguishable functions. Previous studies showed that protein predictors trained on disorder from one type of protein often achieve poor accuracy on disorder of proteins of a different type, thus indicating significant differences in sequence properties among disordered proteins. Important biological problems are identifying different types, or flavors, of disorder and examining their relationships with protein function. Innovative use of computational methods is needed in addressing these problems due to relative scarcity of experimental data and background knowledge related to protein disorder. We developed an algorithm that partitions protein disorder into flavors based on competition among increasing numbers of predictors, with prediction accuracy determining both the number of distinct predictors and the partitioning of the individual proteins. Using 145 variously characterized proteins with long (>30 amino acids) disordered regions, 3 flavors, called V, C, and S, were identified by this approach, with the V subset containing 52 segments and 7743 residues, C containing 39 segments and 3402 residues, and S containing 54 segments and 5752 residues. The V, C, and S flavors were distinguishable by amino acid compositions, sequence locations, and biological function. For the sequences in SwissProt and 28 genomes, their protein functions exhibit correlations with the commonness and usage of different disorder flavors, suggesting different flavor‐function sets across these protein groups. Overall, the results herein support the flavor‐function approach as a useful complement to structural genomics as a means for automatically assigning possible functions to sequences. Proteins 2003;52:573–584. © 2003 Wiley‐Liss, Inc.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>12910457</pmid><doi>10.1002/prot.10437</doi><tpages>12</tpages></addata></record> |
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subjects | Algorithms Archaeal Proteins - chemistry Bacterial Proteins - chemistry Computational Biology - methods Databases, Protein Drosophila Proteins - chemistry Fungal Proteins - chemistry genomics Helminth Proteins - chemistry Plant Proteins - chemistry Protein Conformation Protein Folding Protein Structure, Secondary Proteins - chemistry Reproducibility of Results secondary structure sequence composition signaling and regulatory proteins structure prediction unfolded proteins |
title | Flavors of protein disorder |
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