Document Detail


Stability of the genetic code and optimal parameters of amino acids.
MedLine Citation:
PMID:  20955716     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
The standard genetic code is known to be much more efficient in minimizing adverse effects of misreading errors and one-point mutations in comparison with a random code having the same structure, i.e. the same number of codons coding for each particular amino acid. We study the inverse problem, how the code structure affects the optimal physico-chemical parameters of amino acids ensuring the highest stability of the genetic code. It is shown that the choice of two or more amino acids with given properties determines unambiguously all the others. In this sense the code structure determines strictly the optimal parameters of amino acids or the corresponding scales may be derived directly from the genetic code. In the code with the structure of the standard genetic code the resulting values for hydrophobicity obtained in the scheme "leave one out" and in the scheme with fixed maximum and minimum parameters correlate significantly with the natural scale. The comparison of the optimal and natural parameters allows assessing relative impact of physico-chemical and error-minimization factors during evolution of the genetic code. As the resulting optimal scale depends on the choice of amino acids with given parameters, the technique can also be applied to testing various scenarios of the code evolution with increasing number of codified amino acids. Our results indicate the co-evolution of the genetic code and physico-chemical properties of recruited amino acids.
Authors:
V R Chechetkin; V V Lobzin
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Publication Detail:
Type:  Journal Article     Date:  2010-10-16
Journal Detail:
Title:  Journal of theoretical biology     Volume:  269     ISSN:  1095-8541     ISO Abbreviation:  J. Theor. Biol.     Publication Date:  2011 Jan 
Date Detail:
Created Date:  2010-12-21     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0376342     Medline TA:  J Theor Biol     Country:  England    
Other Details:
Languages:  eng     Pagination:  57-63     Citation Subset:  IM    
Copyright Information:
Copyright © 2010 Elsevier Ltd. All rights reserved.
Affiliation:
Theoretical Department of Division for Perspective Investigations, Troitsk Institute of Innovation and Thermonuclear Investigations (TRINITI), Troitsk, 142190 Moscow Region, Russian Federation.
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