Predicting Binding Regions within Disordered Proteins

Ethan Garner[1] (egarner@disorder.chem.wsu.edu)
Pedro Romero[2] (promero@eecs.wsu.edu)
A. Keith Dunker[1] (dunker@disorder.chem.wsu.edu)
Celeste Brown[1] (celesteb@disorder.chem.wsu.edu)
Zoran Obradovic[2] (zoran@eecs.wsu.edu)

[1] School of Molecular Biosciences
Washington State University, Pullman, WA 99164, U.S.A.
[2] School of Electrical Engineering and Computer Science
Washington State University, Pullman, WA 99164, U.S.A.


Abstract

Disordered regions are sequences within proteins that fail to fold into a fixed tertiary structure and have been shown to be involved in a variety of biological functions. We recently applied neural network predictors of disorder developed from X-ray data to several protein sequences characterized as disordered by NMR (Garner, Cannon, Romero, Obradovic and Dunker, Genome Informatics, 9:201-213, 1998). A few predictions on the NMR-characterized disordered regions were noted to contain "false" negative indications of order that correlated with regions of function. These and additional examples are examined in more detail here. Overall, 8 of 9 functional segments in 5 disordered proteins were identified or partially identified by this approach. The functions of these regions appear to involve binding to DNA, RNA, and proteins. These regions are known to undergo disorder-to-order transitions upon binding. This apparent ability of the predictors to identify functional regions in disordered proteins could be due to the existence of different flavors, or sub-classes of disorder, originating from the sequence of the disordered regions and perhaps owing to local inclinations toward order. These different flavors may be a characteristic that could be used to identify binding regions within proteins that are difficult to characterize structurally.

[ Full-text PDF | Table of Contents ]


Japanese Society for Bioinformatics