Abstract
The methods for protein structure prediction are based on the thermodynamic hypothesis, according to which the free energy of the “protein-solvent” system is minimal in the folded state of protein. By predicting the tertiary protein structure, it is theoretically possible to predict its action. This problem is considered as a global optimization issue. To solve it, a hybrid method based on a combination of clonal selection and differential evolution algorithms is proposed. The variants of protein structures being the subject of the algorithm are represented by a set of torsion angles of the elements of the main and side chains. Evaluation of solution options is carried out using the potential energy function, considering the molecular dynamics of the protein. The effectiveness of the proposed method is confirmed by experimental studies.
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Fefelova, I., Fefelov, A., Lytvynenko, V., Ohnieva, O., Smailova, S. (2022). Prediction of Native Protein Conformation by a Hybrid Algorithm of Clonal Selection and Differential Evolution. In: Babichev, S., Lytvynenko, V. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 77. Springer, Cham. https://doi.org/10.1007/978-3-030-82014-5_21
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DOI: https://doi.org/10.1007/978-3-030-82014-5_21
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