Protein folding problem in the case of peptides solved by hybrid simulated annealing algorithms

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Abstract

Protein Folding Problem (PFP) is a computational challenge with many implications in bioinformatics and computer science. This problem consists in determining the biological and functional three-dimensional structure of the atoms of the amino acid sequence of the protein, which is named Native Structure (NS). Whereas there are a huge number of possible structures this problem is classified as NP-Hard. For PFP, hybrid methods based on Simulated Annealing (SA) have been applied to different kinds of proteins with high-quality solutions. Nevertheless, at the time of presenting this work, they are not enough review of successful algorithms in the group of proteins called peptides. In addition, how successful are the algorithms applied to this kind of proteins has not been previously published. In this paper, we present the main variants of these methods, their applications, and the main characteristics of those algorithms that have made them successful in that area.

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Melo-Vega, A., Frausto-Solís, J., Castilla-Valdez, G., Liñán-García, E., González-Barbosa, J. J., & Terán-Villanueva, D. (2018). Protein folding problem in the case of peptides solved by hybrid simulated annealing algorithms. In Studies in Computational Intelligence (Vol. 749, pp. 141–152). Springer Verlag. https://doi.org/10.1007/978-3-319-71008-2_12

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