Using an alignment of fragment strings for comparing protein structures.

TY - JOUR

T1 - Using an alignment of fragment strings for comparing protein structures.

AU - Friedberg, Iddo

AU - Harder, Tim

AU - Kolodny, Rachel

AU - Sitbon, Einat

AU - Li, Zhanwen

AU - Godzik, Adam

N1 - Keywords: Algorithms; Amino Acid Sequence; Computer Simulation; Models, Chemical; Models, Molecular; Molecular Sequence Data; Peptide Fragments; Peptide Mapping; Protein Conformation; Proteins; Sequence Alignment; Sequence Analysis, Protein

PY - 2007

Y1 - 2007

N2 - MOTIVATION: Most methods that are used to compare protein structures use three-dimensional (3D) structural information. At the same time, it has been shown that a 1D string representation of local protein structure retains a degree of structural information. This type of representation can be a powerful tool for protein structure comparison and classification, given the arsenal of sequence comparison tools developed by computational biology. However, in order to do so, there is a need to first understand how much information is contained in various possible 1D representations of protein structure. RESULTS: Here we describe the use of a particular structure fragment library, denoted here as KL-strings, for the 1D representation of protein structure. Using KL-strings, we develop an infrastructure for comparing protein structures with a 1D representation. This study focuses on the added value gained from such a description. We show the new local structure language adds resolution to the traditional three-state (helix, strand and coil) secondary structure description, and provides a high degree of accuracy in recognizing structural similarities when used with a pairwise alignment benchmark. The results of this study have immediate applications towards fast structure recognition, and for fold prediction and classification.

AB - MOTIVATION: Most methods that are used to compare protein structures use three-dimensional (3D) structural information. At the same time, it has been shown that a 1D string representation of local protein structure retains a degree of structural information. This type of representation can be a powerful tool for protein structure comparison and classification, given the arsenal of sequence comparison tools developed by computational biology. However, in order to do so, there is a need to first understand how much information is contained in various possible 1D representations of protein structure. RESULTS: Here we describe the use of a particular structure fragment library, denoted here as KL-strings, for the 1D representation of protein structure. Using KL-strings, we develop an infrastructure for comparing protein structures with a 1D representation. This study focuses on the added value gained from such a description. We show the new local structure language adds resolution to the traditional three-state (helix, strand and coil) secondary structure description, and provides a high degree of accuracy in recognizing structural similarities when used with a pairwise alignment benchmark. The results of this study have immediate applications towards fast structure recognition, and for fold prediction and classification.

U2 - 10.1093/bioinformatics/btl310

DO - 10.1093/bioinformatics/btl310

M3 - Journal article

C2 - 17237095

SN - 1367-4803

VL - 23

SP - e219-24

JO - Bioinformatics

JF - Bioinformatics

IS - 2

ER -