A new approach to revealing functional residues from analysis of protein primary structure.

A protein's biological function is encrypted within its primary structure. Nevertheless, revealing protein function from analysis of its primary structure is still unsolved problem. In this article we present a new methodology for determining functionally significant amino acid residues in proteins sequences, which is based on time-frequency signal analysis and Smoothed Pseudo Wigner Ville distribution (SPWV). This investigation is the extension of the Resonant Recognition Model (RRM) approach designed for structure-function analysis of proteins and DNA. The RRM is based on the finding that there is a significant correlation between spectra of the numerical presentation of amino acids and their biological activity. The RRM assumes that the selectivity of protein interactions is based on the resonant electromagnetic energy transfer at the specific frequency for each interaction. In this study Cytochrome C, Glucagon, and Hemoglobin proteins were used as the protein examples. By incorporating the SPWV distribution in the RRM, we can define the active regions along the protein molecule. In addition, it was also shown that our computational predictions are corresponding closely with the experimentally identified locations of the active/binding sites for the selected protein examples.