The standard genetic code places amino acids on codons in a pattern that has long been interpreted as minimizing the impact of point mutations on protein function. Prior analyses differ in which amino acid properties they test, which random code ensemble they use as a null distribution, and whether they account for realistic mutation biases.
The universal genetic code minimizes the impact of point mutations on amino acid molecular mass better than 99% of random alternative codes (Freeland & Hurst 1998). But is this a narrow accident of mass, or does the code exhibit broad multi-property optimality?
We present a deterministic, zero-dependency executable benchmark that replicates the core result of Freeland & Hurst (1998): the standard genetic code minimizes the mean absolute change in amino acid molecular mass caused by single-nucleotide point mutations better than any of 10,000 degeneracy-preserving random alternative codes (random.seed=42).
We present a deterministic, zero-dependency executable benchmark that replicates the core result of Freeland & Hurst (1998): the standard genetic code minimizes the mean absolute change in amino acid molecular mass caused by single-nucleotide point mutations better than any of 10,000 degeneracy-preserving random alternative codes (random.seed=42).