Abstract

Abstract

Background: The activity of proteins within the cell is characterized by their motions, flexibility, interactions or even the particularly intriguing case of partially unfolded states. In the last two cases, a part of the protein is affected either by binding or unfolding and the detection of the respective perturbed and unperturbed region(s) is a fundamental part of the structural characterization of these states. This can be achieved by comparing experimental data of the same protein in two different states (bound/unbound, folded/unfolded). For instance, measurements of chemical shift perturbations (CSPs) from NMR 1 H-15 N HSQC experiments gives an excellent opportunity to discriminate both moieties.

Results: We describe an innovative, automatic and unbiased method to distinguish perturbed and unperturbed regions in a protein existing in two distinct states (folded/partially unfolded, bound/unbound). The SAMPLEX program takes as input a set of data and the corresponding three-dimensional structure and returns the confidence for each residue to be in a perturbed or unperturbed state. Its performance is demonstrated for different applications including the prediction of disordered regions in partially unfolded proteins and of interacting regions in protein complexes.

Conclusions: The proposed approach is suitable for partially unfolded states of proteins, local perturbations due to small ligands and protein-protein interfaces. The method is not restricted to NMR data, but is generic and can be applied to a wide variety of information.

Details

Title
SAMPLEX: Automatic mapping of perturbed and unperturbed regions of proteins and complexes
Author
Krzeminski, Mickaël; Loth, Karine; Boelens, Rolf; Bonvin, Alexandre MJJ
Pages
51
Publication year
2010
Publication date
2010
Publisher
BioMed Central
e-ISSN
14712105
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
901868948
Copyright
© 2010 Krzeminski et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.