A Computational Analysis of the Structure of the Genetic Code - Degagne, Christopher (My University, 2015)
The standard genetic code (SGC) is the cipher used by nearly all organisms to transcribe information stored in DNA and translate it into its amino acid counterparts. Since the early 1960s, researchers have observed that the SGC is structured so that similar codons encode amino acids with similar physiochemical properties. This structure has been hypothesized to buffer the SGC against transcription or translational error because single nucleotide mutations usually either are silent or impart minimal effect on the containing protein. We herein briefly review different theories for the origin of that structure. We also briefly review different computational experiments designed to quantify buffering capacity for the SGC. We report on computational Monte Carlo simulations that we performed using a computer program that we developed, AGCT. In the simulations, the SGC was ranked against other, hypothetical genetic codes (HGC) for its ability to minimize physiochemical distances between amino acids encoded by codons separated by single nucleotide mutations. We analyzed unappreciated structural aspects and neglected properties in the SGC. We found that error measure type affected SGC ranking. We also found that altering stop codon positions had no effect on SGC ranking, but including stop codons in error calculations improved SGC ranking. We analyzed 49 properties individually and identified conserved properties. Among these, we found that long-range non-bonded energy is more conserved than is polar requirement, which previously was considered to be the most conserved property in the SGC. We also analyzed properties in combinations. We hypothesized that the SGC is organized as a compromise among multiple properties. Finally, we used AGCT to test whether different theories on the origin of the SGC could explain more convincingly the buffering capacity in the SGC. We found that, without accounting for transition/transversion biases, the SGC ranking was modest enough under constraints imposed by the coevolution and four column theories that it could be explained due to constraints associated with either theory (or both theories); however, when transition/transversion biases were included, only the four column theory returned a SGC ranking modest enough that it could be explained due to constraints associated with that theory.
Keywords: genetic code; evolution; optimality; coevolution; column theory; stop codons; origin of the genetic code; structure of the genetic code; monte carlo simulations