Kuruoglu Ercan E, Arndt Peter F
Institute of Information Science and Technologies, "A. Faedo", CNR, via G Moruzzi 1, 56124 Pisa, Italy.
Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestr. 63/73, 14195 Berlin, Germany.
J Theor Biol. 2017 Apr 21;419:227-237. doi: 10.1016/j.jtbi.2017.01.046. Epub 2017 Feb 3.
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.
我们将分子进化过程视为一个信息传递过程,并根据香农的信道编码定理,从信道容量的角度为信息保存提供了一种定量度量。我们使用各种替换模型,计算了核苷酸水平(针对非编码DNA)和氨基酸水平(针对编码DNA)上DNA的信息容量。我们将编码DNA的研究结果扩展到对天然密码子-氨基酸编码最优性的讨论。我们给出了代码域中自适应搜索算法的结果,并证明存在大量具有更高信息容量的遗传密码。我们的结果支持了一个古老的假说,即从二核苷酸密码子扩展到当前的三核苷酸密码子来编码各种氨基酸。