Parallel Evolutionary Multi-Quenching Annealing for Protein Folding Problem

Authors

  • Anylu Melo Vega Tecnologico Nacional de México- Instituto Tecnológico de Cd. Madero
  • Juan Frausto-Solís Tecnologico Nacional de México- Instituto Tecnológico de Cd. Madero
  • Ernesto Liñán García Universidad Autónoma de Coahuila
  • Guadalupe Castilla Valdez Tecnologico Nacional de México- Instituto Tecnológico de Cd. Madero
  • Juan Javier González Barbosa Tecnologico Nacional de México- Instituto Tecnológico de Cd. Madero
  • David Terán Villanueva Tecnologico Nacional de México- Instituto Tecnológico de Cd. Madero
  • Juan Paulo Sánchez Hernández Universidad Politécnica del Estado de Morelos

Keywords:

Multi-quenching Annealing, Parallel Genetic Algorithms, Protein Folding Problem, Simulated Annealing

Abstract

The Protein Folding Problem (PFP) consists in determining the functional three-dimensional structure or Native Structure (NS) of a protein, which normally has the lowest Gibbs energy. In this paper, a new hybrid Parallel Evolutionary Multi-Quenching Annealing Algorithm (PEMQA) is proposed to obtain high-quality solutions for the target proteins. PEMQA generates an initial population of solutions using a Genetic Algorithm (GA). Furthermore, a Multi-Quenching Algorithm (MQA) is executed in an independent core using each of these Genetic Algorithm (GA) solutions. A master process determines which MQA delivers the best solution. PEMQA uses shared memory parallel programming and is implemented in SMMP (Simple Molecular Mechanics for Proteins). The incorporation of evolutionary processes in a PEMQA algorithm allows an improvement in MQA capacity of exploration. Results obtained with PEMQA outperform most of those achieved by the classic SA reported in current state of the art literature.

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Published

2018-06-19

How to Cite

Melo Vega, A., Frausto-Solís, J., Liñán García, E., Castilla Valdez, G., González Barbosa, J. J., Terán Villanueva, D., & Sánchez Hernández, J. P. (2018). Parallel Evolutionary Multi-Quenching Annealing for Protein Folding Problem. International Journal of Combinatorial Optimization Problems and Informatics, 9(3), 41–54. Retrieved from https://www.ijcopi.org/ojs/article/view/100

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