WHICH EFFECTIVE PROPERTY OF AMINO-ACIDS IS BEST PRESERVED BY THE GENETIC-CODE

Simple procedures are proposed to quantify how much an effective prope rty embodied in a given ranking of the twenty amino acids can be affec ted by random point mutations at nucleotide bases. As expected, of the various orderings tested, rankings based on most hydrophobicity scale s exhibit low scores, thus offering better immunity towards such singl e-base mutations. This, however, occurs to different extents and the m ethod allows sharp discriminations between the scales. Hydrophobicity scales based on global properties such as spatial environment data of proteins residues, or mutation matrices of amino acid replacements, ge nerally behave better than those based on pure physicochemical propert ies of isolated residues. An averaged scale built from the available h ydrophobicity scales exhibits one of the most favorable scores. A syst ematic search for the best amino acid order has been carried out acros s all possible scales. Optimized scales are characterized by the exist ence of a clustering scheme into three zones, within which permutation s are more or less tolerated, depending on the zone and on the summati on procedure used in the score calculation, The first cluster correspo nds to the hydrophobic side, and includes the ten amino acids WMCFILVG RS, Next follows the ATP triad. The third cluster coincides with the h ydrophilic side and includes, in the last seven positions, the amino a cids EDKNQHY. Interpretation of these optimized scales in terms of cod on positions in the genetic code further suggests a clustering scheme composed of four groups, WMCFILV-GRS-ATP-EDKNQHY, emphasizing the role of the second base as the main driving parameter. As a consequence, t he conserved character of the genetic code is better reflected when it is displayed in UGCA ordering rather than in the commonly used UCAG o rdering. The present a priori classification of the amino acids could find potential use in protein sequence homology and structure predicti on.