Abstract
In this work we investigate the applicability of a multiobjective formulation of the Ab-Initio Protein Structure Prediction (PSP) to medium size protein sequences (46-70 residues). In particular, we introduce a modified version of Pareto Archived Evolution Strategy (PAES) which makes use of immune inspired computing principles and which we will denote by “I-PAES”. Experimental results on the test bed of five proteins from PDB show that PAES, (1+1)-PAES and its modified version I-PAES, are optimal multiobjective optimization algorithms and the introduced mutation operators, mut 1 and mut 2, are effective for the PSP problem. The proposed I-PAES is comparable with other evolutionary algorithms proposed in literature, both in terms of best solution found and computational cost.
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Cutello, V., Narzisi, G., Nicosia, G. (2005). A Class of Pareto Archived Evolution Strategy Algorithms Using Immune Inspired Operators for Ab-Initio Protein Structure Prediction. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32003-6_6
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DOI: https://doi.org/10.1007/978-3-540-32003-6_6
Publisher Name: Springer, Berlin, Heidelberg
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