Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

Open Access Highly Accessed Methodology article

Dynamics based alignment of proteins: an alternative approach to quantify dynamic similarity

Márton Münz123, Rune Lyngsø2, Jotun Hein23 and Philip C Biggin13*

Author Affiliations

1 Structural Bioinformatics and Computational Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK

2 Department of Statistics, University of Oxford, 1 South Parks Road, Oxford, OX1 3TG, UK

3 Oxford Centre for Integrative Systems Biology, Department of Biochemistry, South Parks Road, Oxford, OX1 3QU, UK

For all author emails, please log on.

BMC Bioinformatics 2010, 11:188  doi:10.1186/1471-2105-11-188

Published: 14 April 2010

Abstract

Background

The dynamic motions of many proteins are central to their function. It therefore follows that the dynamic requirements of a protein are evolutionary constrained. In order to assess and quantify this, one needs to compare the dynamic motions of different proteins. Comparing the dynamics of distinct proteins may also provide insight into how protein motions are modified by variations in sequence and, consequently, by structure. The optimal way of comparing complex molecular motions is, however, far from trivial. The majority of comparative molecular dynamics studies performed to date relied upon prior sequence or structural alignment to define which residues were equivalent in 3-dimensional space.

Results

Here we discuss an alternative methodology for comparative molecular dynamics that does not require any prior alignment information. We show it is possible to align proteins based solely on their dynamics and that we can use these dynamics-based alignments to quantify the dynamic similarity of proteins. Our method was tested on 10 representative members of the PDZ domain family.

Conclusions

As a result of creating pair-wise dynamics-based alignments of PDZ domains, we have found evolutionarily conserved patterns in their backbone dynamics. The dynamic similarity of PDZ domains is highly correlated with their structural similarity as calculated with Dali. However, significant differences in their dynamics can be detected indicating that sequence has a more refined role to play in protein dynamics than just dictating the overall fold. We suggest that the method should be generally applicable.