ArticleJournal of molecular evolution2010
Searching of code space for an error-minimized genetic code via codon capture leads to failure, or requires at least 20 improving codon reassignments via the ambiguous intermediate mechanism.
Article in Journal of molecular evolution, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A crescendo of competent coding (c3) contains the Standard Genetic Code.RNA (New York, N.Y.) · 2022Article
- Genetic Code Error Minimization as a Non-Adaptive But Beneficial Trait.Journal of molecular evolution · 2019Article
- Genetic code evolution reveals the neutral emergence of mutational robustness, and information as an evolutionary constraint.Life (Basel, Switzerland) · 2015Article
- A nonadaptive origin of a beneficial trait: in silico selection for free energy of folding leads to the neutral emergence of mutational robustness in single domain proteins.Journal of molecular evolution · 2014Article
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1 author.
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Abstract
The standard genetic code (SGC) has a fundamental error-minimizing property which has been widely attributed to the action of selection. However, a clear mechanism for how selection can give rise to error minimization (EM) is lacking. A search through a space of alternate codes (code space) via codon reassignments would be required, to select a code optimized for EM. There are two commonly discussed mechanisms of codon reassignment; the Codon Capture mechanism, which proposes a loss of the codon during reassignment, and the Ambiguous Intermediate mechanism, which proposes that the codon underwent an ambiguous phase during reassignment. When searching of code space via the Codon Capture mechanism is simulated, an optimized genetic code can rarely be achieved (0-3.2% of the time) with most searches ending in failure. When code space is searched via the Ambiguous Intermediate mechanism, under constraints derived from empirical observations of codon reassignments from extant genomes, the searches also often end in failure. When a local minimum is avoided and optimization is achieved, 20-41 sequential improving codon reassignments are required. Furthermore, the structures of the optimized codes produced by these simulations differ from the structure of the SGC. These data are challenges for the Adaptive Code hypothesis to address, which proposes that the EM property was directly selected for, and suggests that EM is simply a byproduct of the addition of amino acids to the expanding code, as described by the alternative 'Emergence' hypothesis.
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