Inferring function using patterns of native disorder in proteins.
PLOS COMPUT BIOL
, Article e162. 10.1371/journal.pcbi.0030162.
Natively unstructured regions are a common feature of eukaryotic proteomes. Between 30% and 60% of proteins are predicted to contain long stretches of disordered residues, and not only have many of these regions been confirmed experimentally, but they have also been found to be essential for protein function. In this study, we directly address the potential contribution of protein disorder in predicting protein function using standard Gene Ontology ( GO) categories. Initially we analyse the occurrence of protein disorder in the human proteome and report ontology categories that are enriched in disordered proteins. Pattern analysis of the distributions of disordered regions in human sequences demonstrated that the functions of intrinsically disordered proteins are both length- and positiondependent. These dependencies were then encoded in feature vectors to quantify the contribution of disorder in human protein function prediction using Support Vector Machine classifiers. The prediction accuracies of 26 GO categories relating to signalling and molecular recognition are improved using the disorder features. The most significant improvements were observed for kinase, phosphorylation, growth factor, and helicase categories. Furthermore, we provide predicted GO term assignments using these classifiers for a set of unannotated and orphan human proteins. In this study, the importance of capturing protein disorder information and its value in function prediction is demonstrated. The GO category classifiers generated can be used to provide more reliable predictions and further insights into the behaviour of orphan and unannotated proteins.
|Title:||Inferring function using patterns of native disorder in proteins|
|Open access status:||An open access version is available from UCL Discovery|
|Additional information:||© 2007 Lobley et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was funded in part by Inpharmatica, and the European Commission within its FP6 Programme, under the thematic area “Life sciences, genomics, and biotechnology for health,” contract LHSG-CT-2003–503265 (BioSapiens Network of Excellence).|
|Keywords:||INTRINSICALLY UNSTRUCTURED PROTEINS, AMINO-ACID-SEQUENCE, GENE ONTOLOGY, STRUCTURAL DISORDER, FUNCTION PREDICTION, PEST MOTIFS, FLEXIBILITY, PHOSPHORYLATION, LOCALIZATION, ALIGNMENTS|
|UCL classification:||UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Biosciences (Division of)
UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Biosciences (Division of) > Structural and Molecular Biology
UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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