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Glocal: Reconstructing Protein 3D Structure from 2D Contact Map by Combining Global and Local Optimization Schemes

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Prediction of protein 3D structure from solely its amino acid sequence is one of the most challenging problems in structural bioinformatics, where the 3D structure reconstruction from observed constraints is the key step. In this paper, we propose a novel protocol called Glocal to recover a protein’s 3D coordinates based on a given 2D contact map by combining both global and local optimization schemes achieved by the swarm intelligence of Particle Swarm Optimization (PSO) and the Simulated Annealing (SA) techniques respectively. Our results demonstrate that Glocal can recover the 3D structures with the average RMSD less than 2 Å from the native contact map. Further analysis also shows that Glocal is powerful for handling with noisy contact map with the proposed combination optimization approaches.
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Keywords: Glocal; Simulated Annealing; Threshold; particle swarm optimization; protein; protein contact map; protein structure reconstruction; resolutions; simulated annealing

Document Type: Research Article

Affiliations: Department of Automation, Shanghai Jiao Tong University, Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, 200240, China.

Publication date: 01 June 2012

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