alexa Meta-analysis of Protein Structural Alignment | OMICS International | Abstract
ISSN: 0974-276X

Journal of Proteomics & Bioinformatics
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Research Article

Meta-analysis of Protein Structural Alignment

Jim Havrilla* and Ahmet Saçan

School of Biomedical Engineering Drexel University, Philadelphia, PA, USA

*Corresponding Author:
Jim Havrilla
School of Biomedical Engineering Drexel University
Philadelphia, PA, USA
E-mail: [email protected], [email protected]

Received date: July 03, 2013; Accepted date: August 22, 2013; Published date: August 28, 2013

Citation: Havrilla J, Saçan A (2013) Meta-analysis of Protein Structural Alignment. J Proteomics Bioinform 6: 171-175. doi: 10.4172/jpb.1000277

Copyright: © 2013 Havrilla J, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The three-dimensional structure of a protein molecule provides significant insight into its biological function. Structural alignment of proteins is an important and widely performed task in the analysis of protein structures, whereby functionally and evolutionarily important segments are identified. However, structural alignment is a computationally difficult problem and a large number of heuristics introduced to solve it do not agree on their results. Consequently, there is no widely accepted solution to the structure alignment problem. In this study, we present a meta-analysis approach to generate a re- optimized, best-of-all result using the alignments generated from several popular methods. Evaluations of the methods on a large set of benchmark pairwise alignments indicate that TMalign (Template Modeling Alignment) provides superior alignments (except for RMSD, root mean square deviation), compared to other methods we have surveyed. Smolign (Spatial Motifs Based Multiple Protein Structure Alignment) provides smaller cores than other methods with best RMSD values. The re-optimization of the alignments using TM-align’s optimization method does not alter the relative performance of the methods. Additionally, visualization approaches to delineate the relationships of the alignment methods have been performed and their results provided

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