Comparative study of computational strategies for protein structure prediction

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Abstract

Protein Folding Problem (PFP) is one of the most challenging problems of combinatorial optimization with applications in bioinformatics and molecular biology. The aim of PFP is to find the three-dimensional structure of a protein, this structure is known as Native Structure (NS), which is characterized by the minimal energy of Gibbs and it is commonly the best functional structure. To find an NS knowing only the amino acids sequence (primary structure) of a protein is known as ab initio problem. A protein can take a huge number of different conformational structures from its primary structure to the NS. For solving PFP, several computational strategies are applied in order to search structures of protein on a huge space of possible solutions. In this work, the most popular methods and strategies are compared, and advantages and disadvantages of them are discussed.

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Maldonado-Nava, F. G., Frausto-Solís, J., Sánchez-Hernández, J. P., González Barbosa, J. J., & Liñán-García, E. (2018). Comparative study of computational strategies for protein structure prediction. In Studies in Computational Intelligence (Vol. 749, pp. 449–459). Springer Verlag. https://doi.org/10.1007/978-3-319-71008-2_32

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