Extremal Optimization for protein folding simulations on the lattice

Authors:
Hengyun Lu;Genke Yang
Affiliations:
School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University Shanghai, 200240, Shanghai, China;School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University Shanghai, 200240, Shanghai, China
Venue:
Computers & Mathematics with Applications
Year:
2009

Citing 2
Cited 1

Extremal optimization: heuristics via coevolutionary avalanches

Computing in Science and Engineering
A complete and effective move set for simplified protein folding

RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology

Memory-based local search for simplified protein structure prediction

Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine

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Abstract

This paper presents a novel guided search strategy Extremal Optimization (EO) with constrained structure for protein folding. In the proposed algorithm, evaluating the fitness of each monomer in an amino-acid sequence is introduced to guide the improvement of the conformation. In addition, a constrained structure is proposed to reduce the complexity of algorithm. We demonstrate that EO can be applied successfully to the protein folding problem. The results show that the algorithm can find the best solutions so far for the listed benchmarks. Within the achieved results, the search converged rapidly and efficiently.