Title :
Optimal protein structure alignment using modified extremal optimization
Author :
Nakada, Akihiro ; Tamura, Keiichi ; Kitakami, Hajime
Author_Institution :
Grad. Sch. of Inf. Sci., Hiroshima City Univ., Hiroshima, Japan
Abstract :
Proteins are important biochemical compounds that have biogenic functions for biological activities. The three-dimensional structures of proteins are closely related to its biological functions, and therefore, techniques for comparing them have been studied. Many of these techniques for comparing protein structures are based on protein structure alignment, which is one of the most effective methods. CMO (Contact Map Overlap) is formulated as combinatorial optimization to find the optimal structure alignments. In this paper, we propose a novel heuristic using Modified Extremal Optimization (MEO) for CMO. Our MEO-based heuristic is characterized by three features. First, the proposed heuristic uses MEO for alternation generations. Second, an initial solution is created by dynamic programming (DP). Third, state transition is executed using the best admissible move strategy.
Keywords :
bioinformatics; combinatorial mathematics; dynamic programming; evolutionary computation; heuristic programming; molecular biophysics; molecular configurations; proteins; 3D protein structures; CMO; MEO-based heuristic; alternation generations; best admissible move strategy; biogenic functions; biological activities; combinatorial optimization; contact map overlap; dynamic programming; modified extremal optimization; protein structure alignment; state transition; Amino acids; Databases; Heuristic algorithms; Linear programming; Nickel; Optimization; Proteins; bioinformatics; contact map overlap problem; evolutionary computation; extremal optimization; protein structure alignment;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
DOI :
10.1109/ICSMC.2012.6377808