Abstract
BackgroundThe standard genetic code (SGC) is a unique set of rules which assign amino acids to codons. Similar amino acids tend to have similar codons indicating that the code evolved to minimize the costs of amino acid replacements in proteins, caused by mutations or translational errors. However, if such optimization in fact occurred, many different properties of amino acids must have been taken into account during the code evolution. Therefore, this problem can be reformulated as a multi-objective optimization task, in which the selection constraints are represented by measures based on various amino acid properties.ResultsTo study the optimality of the SGC we applied a multi-objective evolutionary algorithm and we used the representatives of eight clusters, which grouped over 500 indices describing various physicochemical properties of amino acids. Thanks to that we avoided an arbitrary choice of amino acid features as optimization criteria. As a consequence, we were able to conduct a more general study on the properties of the SGC than the ones presented so far in other papers on this topic. We considered two models of the genetic code, one preserving the characteristic codon blocks structure of the SGC and the other without this restriction. The results revealed that the SGC could be significantly improved in terms of error minimization, hereby it is not fully optimized. Its structure differs significantly from the structure of the codes optimized to minimize the costs of amino acid replacements. On the other hand, using newly defined quality measures that placed the SGC in the global space of theoretical genetic codes, we showed that the SGC is definitely closer to the codes that minimize the costs of amino acids replacements than those maximizing them.ConclusionsThe standard genetic code represents most likely only partially optimized systems, which emerged under the influence of many different factors. Our findings can be useful to researchers involved in modifying the genetic code of the living organisms and designing artificial ones.
Highlights
The standard genetic code (SGC) is a unique set of rules which assign amino acids to codons
As the objectives in the genetic code optimization we considered the costs of all possible changes from one amino acid to another caused by single-point mutations in codons
The values smaller than 50% indicate that the SGC shows a tendency to minimize rather than maximize the costs of amino acid replacements under a given criterion
Summary
The standard genetic code (SGC) is a unique set of rules which assign amino acids to codons. Similar amino acids tend to have similar codons indicating that the code evolved to minimize the costs of amino acid replacements in proteins, caused by mutations or translational errors If such optimization occurred, many different properties of amino acids must have been taken into account during the code evolution. The coevolution hypothesis claims that the present structure of the SGC is a reflection of the expansion of prebiotic pathways for the biosynthesis of amino acids [14,15,16,17,18,19,20,21] According to this scenario, the SGC evolved from its ancestral form, which encoded only a small number of amino acids produced by simple biochemical reactions. In the consecutive evolutionary stages other amino acids were incorporated into the code simultaneously with the evolution of more complex metabolic networks
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