title: Prediction of intrinsic disorder in proteins using MFDp2.
abstract: Intrinsically disordered proteins (IDPs) are either entirely disordered or contain disordered regions in their native state. IDPs were found to be abundant across all kingdoms of life, particularly in eukaryotes, and are implicated in numerous cellular processes. Experimental annotation of disorder lags behind the rapidly growing sizes of the protein databases and thus computational methods are used to close this gap and to investigate the disorder. MFDp2 is a novel webserver for accurate sequence-based prediction of protein disorder which also outputs well-described sequence-derived information that allows profiling the predicted disorder. We conveniently visualize sequence conservation, predicted secondary structure, relative solvent accessibility, and alignments to chains with annotated disorder. The webserver allows predictions for multiple proteins at the same time, includes help pages and tutorial, and the results can be downloaded as text-based (parsable) file. MFDp2 is freely available at http://biomine.ece.ualberta.ca/MFDp2/.
authors.affiliation: Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.
authors.forename: Marcin J
authors.initials: MJ
authors.lastname: Mizianty
authors.forename: Vladimir
authors.initials: V
authors.lastname: Uversky
authors.forename: Lukasz
authors.initials: L
authors.lastname: Kurgan
mesh_terms: D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D064267:Intrinsically Disordered Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D064878:Web Browser
chemical_list: D064267:Intrinsically Disordered Proteins