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Advances in Bioinformatics
Volume 2010, Article ID 454671, 8 pages
Research Article

A Signal Processing Method to Explore Similarity in Protein Flexibility

1Department of Computer Science, Virginia Commonwealth University, Richmond, VA 23284, USA
2Department of Computer Science, Bowie State University, Bowie, MD 20715, USA
3Department of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA

Received 21 January 2010; Revised 16 August 2010; Accepted 24 September 2010

Academic Editor: Alejandro Schäffer

Copyright © 2010 Simina Vasilache et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM) provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods.