The information capacity of the genetic code: Is the natural code optimal?

Kuruoglu, E. E.; Arndt, P. F.

doi:10.1016/j.jtbi.2017.01.046

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The information capacity of the genetic code: Is the natural code optimal?

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Arndt, P. F.
Evolutionary Genomics (Peter Arndt), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

Kuruoglu, E. E., & Arndt, P. F. (2017). The information capacity of the genetic code: Is the natural code optimal? Journal of Theoretical Biology, 419, 227-237. doi:10.1016/j.jtbi.2017.01.046.

Cite as: https://hdl.handle.net/21.11116/0000-0000-7D7E-8

Abstract

We envision the molecular evolution process as an information transfer process and provide a quantitative measure for information preservation in terms of the channel capacity according to the channel coding theorem of Shannon. We calculate Information capacities of DNA on the nucleotide (for non-coding DNA) and the amino acid (for coding DNA) level using various substitution models. We extend our results on coding DNA to a discussion about the optimality of the natural codon-amino acid code. We provide the results of an adaptive search algorithm in the code domain and demonstrate the existence of a large number of genetic codes with higher information capacity. Our results support the hypothesis of an ancient extension from a 2-nucleotide codon to the current 3-nucleotide codon code to encode the various amino acids.