首页> 外文期刊>Journal of Molecular Evolution >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
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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

机译:通过密码子捕获在错误代码最小的遗传密码中搜索代码空间会导致失败,或者至少需要通过模棱两可的中间机制改善密码子的重新分配

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摘要

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.
机译:标准遗传密码(SGC)具有最小化错误的基本属性,该属性已广泛归因于选择的作用。但是,缺少一种明确的机制来选择如何使错误最小化(EM)。需要通过密码子重新分配在替代代码空间(代码空间)中进行搜索,以选择针对EM优化的代码。密码子重新分配有两种通常讨论的机制:密码子捕获机制(建议在重新分配期间丢失密码子)和歧义中间机制(建议在重新分配期间使密码子经历歧义阶段)。当模拟通过密码子捕获机制进行的代码空间搜索时,很少会获得优化的遗传密码(0-3.2%的时间),而大多数搜索都以失败告终。当通过歧义中间机制搜索代码空间时,在根据对现存基因组密码子重新分配的经验观察得出的约束下,搜索通常也以失败告终。当避免局部最小值并实现优化时,需要20-41个顺序的改进密码子重新分配。此外,通过这些模拟产生的优化代码的结构与SGC的结构不同。这些数据是自适应密码假设要解决的挑战,该假设建议直接针对EM属性进行选择,并表明EM只是扩展代码中添加氨基酸的副产品,如备用Emergence假设所述。

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