Resonant recognition model and protein topography

Abstract

This study describes the further extension of the resonant recognition model for the analysis and prediction of protein--protein and protein--DNA structure/function dependencies. The model is based on the significant correlation between spectra of numerical presentations of the amino acid or nucleotide sequences of proteins and their coded biological activity. According to this physico-mathematical method, it is possible to define amino acids in the sequence which are predicted to be the most critical for protein function. Using sperm whale myoglobin, human hemoglobin and hen egg white lysozyme as model protein examples, sets of predicted amino acids, or so-called 'hot spots', have been identified within the tertiary structure. It was found for each protein that the predicted 'hot spots', which are distributed along the primary sequence, are spatially grouped in a dome-like arrangement over the active site. The identified amino acids did not correspond to the amino acid residues which are involved in the chemical reaction site of these proteins. It is thus proposed that the resonant recognition model helps to identify amino acid residues which are important for the creation of the molecular structure around the catalytic active site and also the associated physical field conditions required for biorecognition, docking of the specific substrate and full biological activity.