Protein evolution: the deciphering of latent facets - correlation of synthesis profiles of ribosomally directed proteins and enzyme directed peptides

Key facets pertaining to the evolution of proteins have been probed, using as springboard, the relevant data bases constructed from (i) 60 ribosomally directed proteins, whose 3D structures are known and having 10,000 residues and (ii) from 73 enzyme directed peptides, comprising of 524 residues. The preference profiles, both in terms of the choice of neighbours and the placement of the peptide bonds, have been delineated with respect to each of the 20 coded amino acids. By and large, the preference profile from both the sets are similar, thus giving importance to the nature of the side chains of the coded amino acids. The predictive power of the preference profile has been tested with good results, thus demonstrating the evidence of common preference pathways for peptide formation during evolution. The ribosomally directed protein synthesis, controlled by the genome, proceeds by the addition of single residues at a time. On the other hand, the enzyme directed peptide synthesis largely operates in a more energy conscious block mode, where each constituent of a large enzyme ensemble is engaged in precisely assembling the modules and transfering them to the adjacent one, thus realizing a sequence specific peptide synthesis. Of significance is the fact that, in spite of such divergence in assembly, predictions for neighbour preferences in ribosomally directed protein synthesis work well when applied to enzyme directed peptide synthesis. The findings here are significant since they provide (i) a clear picture of directed peptide synthesis in the absence of direct genomic control, (ii) evidence for the preferred formation of peptide bonds using protein templates, (iii) they also provide evidence for the presence of protein like structures, with catalytic activity, prior to the freezing of the genetic code arising from dominance of the information system and (iv) a logical approach to the evolution of a hierarchical pattern