Use of Chou-Fasman amino acid conformational parameters to analyze the organization of the genetic code and to construct protein genealogies

Morris Goodman, G. William Moore

Research output: Contribution to journalArticlepeer-review

Abstract

Chou-Fasman parameters, measuring preferences of each amino acid for different conformational regions in proteins, were used to obtain an amino acid difference index of conformational parameter distance (CPD) values. CPD values were found to be significantly lower for amino acid exchanges representing in the genetic code transitions of purines, G⇆A than for exchanges representing either transitions of pyrimidines, C⇆U, or transversions of purines and pyrimidines. Inasmuch as the distribution of CPD values in these non G⇆A exchanges resembles that obtained for amino acid pairs with double or triple base differences in their underlying codons, we conclude that the genetic code was not particularly designed to minimize effects of mutation on protein conformation. That natural selection minimizes these changes, however, was shown by tabulating results obtained by the maximum parsimony method for eight protein genealogies with a total occurrence of 4574 base substitutions. At the beginning position of the codons G⇆A transitions were in very great excess over other base substitutions, and, conversely, C⇆U transitions were deficient. At the middle position of the codons only fast evolving proteins showed an excess of G⇆A transitions, as though selection mainly preserved conformation in these proteins while weeding out mutations affecting chemical properties of functional sites in slow evolving proteins. In both fast and slow evolving proteins the net direction of transitions and transversions was found to be from G beginning codons to non-G beginning codons resulting in more commonly occurring amino acids, especially alanine with its generalized conformational properties, being replaced at suitable sites by amino acids with more specialized conformational and chemical properties. Historical circumstances pertaining to the origin of the genetic code and the nature of primordial proteins could account for such directional changes leading to increases in the functional density of proteins. In order to further explore the course of protein evolution, a modified parsimony algorithm was developed for constructing protein genealogies on the basis of minimum CPD length. The algorithm's ability to judge with finer discrimination that in protein evolution certain pathways of amino acid substitution should occur more readily than others was considered a potential advantage over strict maximum parsimony. In developing this CPD algorithm, the path of minimum CPD length through intermediate amino acids allowed by the genetic code for each pair of amino acids was determined. It was found that amino acid exchanges representing two base changes have a considerably lower average CPD value per base substitution than the amino acid exchanges representing single base changes. Amino acid exchanges representing three base changes have yet a further marked reduction in CPD per base change. This shows how extreme constraining effects of stabilizing selection can be circumvented, for by way of intermediate amino acids almost any amino acid can ultimately be substituted for another without damage to an evolving protein's conformation during the process.

Original languageEnglish (US)
Pages (from-to)7-47
Number of pages41
JournalJournal of Molecular Evolution
Volume10
Issue number1
DOIs
StatePublished - 1977
Externally publishedYes

Keywords

  • Amino acid conformational parameters
  • Genetic code
  • Maximum parsimony method
  • Protein evolution
  • Protein genealogies
  • Substitution frequencies
  • Transitions
  • Transversions

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Ecology, Evolution, Behavior and Systematics
  • Biochemistry, Genetics and Molecular Biology(all)
  • Biochemistry
  • Genetics
  • Molecular Biology
  • Genetics(clinical)

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