Multiobjective Evolutionary Algorithms Applied to the Optimization of Expanded Genetic Codes

• Maísa de Carvalho Silva USP
• Paulo Guilherme Pinheiro Pereira USP
• Lariza Laura de Oliveira USP https://orcid.org/0000-0002-5098-172X
• Renato Tinós USP https://orcid.org/0000-0003-4027-8851

Resumo

There is great interest in the creation of genetically modified organisms that use amino acids different from the naturally encoded amino acids. Unnatural amino acids have been incorporated into genetically modified organisms to develop new drugs, fuels and chemicals. When incorporating new amino acids, it is necessary to change the standard genetic code. Expanded genetic codes have been created without considering the robustness of the code. In this work, multi-objective genetic algorithms are proposed for the optimization of expanded genetic codes. Two different approaches are compared: weighted and Pareto. The expanded codes are optimized in relation to the frequency of replaced codons and two measures based on robustness (for polar requirement and molecular volume). The experiments indicate that multi-objective approaches allow to obtain a list of expanded genetic codes optimized according to combinations of the three objectives. Thus, specialists can choose an optimized solution according to their needs.