title: Computational resources for the prediction and analysis of native disorder in proteins.
abstract: Proteomics attempts to characterise the gene products expressed in a cell or tissue via a range of biophysical techniques including crystallography and NMR and, more relevantly to this volume, chromatography and mass spectrometry. It is becoming increasingly clear that the native states of segments of many of the cellular proteins are not stable, folded structures, and much of the proteome is in an unfolded, disordered state. These proteins and their disordered segments have functionally interesting properties and provide novel challenges for the biophysical techniques that are used to study them. This chapter focuses on computational approaches to predicting such regions and analyzing the functions linked to them, and has implications for protein scientists who wish to study such properties as molecular recognition and post-translational modifications. We also discuss resources where the results of predictions have been collated, making them publicly available to the wider biological community.
authors.affiliation: Department of Computer Science, University College London, Gower Street, London, UK.
authors.forename: Melissa M
authors.initials: MM
authors.lastname: Pentony
authors.forename: Jonathan
authors.initials: J
authors.lastname: Ward
authors.forename: David T
authors.initials: DT
authors.lastname: Jones
mesh_terms: D030562:Databases, Protein; D004194:Disease / Q000209:etiology*; D016678:Genome; D006801:Humans; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000032:analysis* / Q000378:metabolism; D040901:Proteomics / Q000379:methods*
chemical_list: D011506:Proteins