Protein Structure and Function: Application of Bioinformatics Methods - John Rigden 2014

Bioinformatics Methods for Studying the Structure and Function of Unordered Proteins
Prediction of Disorder

Based on these compositional features, about 25 Structure/76.html">Disorder Prediction Methods have been developed (see Table 5.1 (Ferron et al. 2006; Dosztanyi et al. 2007)). The best prediction methods approach the accuracy of top Secondary structure prediction algorithms, and the principles for comparing their performance have already been outlined.

Class="center">Table 5.1. Disorder prediction software. The table lists the most commonly used programs, their URLs, and the principles underlying them. A detailed description of these programs can be found in the text and References (Ferron et al. 2006; Dosztanyi et al. 2007)

Name

URL

Operating principle

PONDR VSL2

http://www.ist.temple.edu/disprot/predictorVSL2.php

Support vector machine with a nonlinear kernel

DISOPRED2

http://bioinf.cs.ucl.ac.uk/disopred

Support vector machine, neural networks for smoothing

IUPred

http://iupred.enzim.hu

Pairwise interaction energy estimation

DisEMBL

http://dis.embl.de

Neural network

GlobPlot

http://globplot.embl.de

Propensity of amino acid residues to form specific secondary structure types

FoldUnfold

http://skuld.protres.ru/~mlobanov/ogu/ogu.cgi

Amino acid residue propensity

Foldlndex

http://bip.weizmann.ас.іl/fldbin/findex

Amino acid residue propensity

NORSp

http://cubic.bioc.columbia.edu/services/NORSp

Secondary structure type propensity

PreLink

http://Genomics.eu.org/spip/PreLink

Amino acid residue propensity + hydrophobic cluster analysis


Last update: 06/08/2026

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