title: A signal processing method to explore similarity in protein flexibility.
abstract: 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.
authors.affiliation: Department of Computer Science, Virginia Commonwealth University, Richmond, VA 23284, USA.
authors.forename: Simina
authors.initials: S
authors.lastname: Vasilache
authors.forename: Nazanin
authors.initials: N
authors.lastname: Mirshahi
authors.forename: Soo-Yeon
authors.initials: SY
authors.lastname: Ji
authors.forename: James
authors.initials: J
authors.lastname: Mottonen
authors.forename: Donald J
authors.initials: DJ
authors.lastname: Jacobs
authors.forename: Kayvan
authors.initials: K
authors.lastname: Najarian