Optimality of the genetic code with respect to protein stability and amino-acid frequencies
By Dimitri Gilis, Serge Massar, Nicolas J. Cerf, Marianne Rooman. 2001
202 citations recorded by the source corpus.
BackgroundThe genetic code is known to be efficient in limiting the effect of mistranslation errors. A misread codon often codes for the same amino acid or one with similar biochemical properties, so the structure and function of the coded protein remain relatively unaltered. Previous studies have attempted to address this question quantitatively, by estimating the fraction of randomly generated codes that do better than the genetic code in respect of overall robustness. We extended these results by investigating the role of amino-acid frequencies in the optimality of the genetic code.ResultsWe found that taking the amino-acid frequency into account decreases the fraction of random codes that beat the natural code. This effect is particularly pronounced when more refined measures of the amino-acid substitution cost are used than hydrophobicity. To show this, we devised a new cost function by evaluating in silico the change in folding free energy caused by all possible point mutations in a set of protein structures. With this function, which measures protein stability while being unrelated to the code's structure, we estimated that around two random codes in a billion (109) are fitter than the natural code. When alternative codes are restricted to those that interchange biosynthetically related amino acids, the genetic code appears even more optimal.ConclusionsThese results lead us to discuss the role of amino-acid frequencies and other parameters in the genetic code's evolution, in an attempt to propose a tentative picture of primitive life.
Subfields: Molecular Biology
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In Molecular Biology
- Shalev Itzkovitz
- Uri Alon
- Artem S. Novozhilov
- Eugene V. Koonin
- Sahand Hormoz
- Olaf Sporns
- Falk Schreiber
- Manolis Kellis
Citations in the corpus
- Amino acid composition of proteins reduces deleterious impact of mutations (2013, methodology): “We can think of these A sequences as drawing A numbers independently from the distribution in Eq.(1).”
- Origin and evolution of the genetic code: the universal enigma (2008, background): “for an amino acid and the frequency of the amino acid in proteins (15, 16); the apparent minimization of the likelihood of mistranslation and point mutations (17, 18); and the near”
- The genetic code is nearly optimal for allowing additional information within protein-coding sequences. (2007, background): “This feature has been attributed to an adaptive selection of a code, so that errors that misread a codon by one letter would result in minimal effects on the translated protein (Freeland and Hurst 1998; Freeland et al. 2000; Gilis et al. 2001; Wagner 2005b).”