Hybrid approach to analysis of β-sheet structures based on signal processing and statistical consideration

Abstract

A number of biotechnology applications are based on protein design. For this design, the relationship between a protein’s primary structure and its conformation is of vital importance. A β-sheet is a common feature of a protein’s two-dimensional structure; therefore, elucidating the principles governing β-sheet structure and its stability is critical for understanding the protein-folding process. In the three-dimensional representation of protein molecules, C α carbon coordinates (carbon atom immediately adjacent to the carboxylate group) have often been employed instead of the complete set of coordinates for the corresponding residues. Using the C α carbon coordinates, we showed that particular amino acids are not randomly distributed within a β-sheet structure. On the basis of a new statistical approach for the analysis of a spatial distribution of amino acids in a protein, presented by their physico-chemical parameters, the electron–ion interaction potential (EIIP) and hydrophobicity, are described here. The relationship between amino acid positions inside the β-sheet and the EIIP and hydrophobicity parameters was established. The correlation between amino acid propensities related to the β-sheet was examined using multiple cross-spectra analysis. We also applied the continuous wavelet transform for the analysis of selected β-sheet structures using the EIIP and hydrophobicity parameters. The findings provide new insight into conformational propensities of amino acids for the adaption of β-sheet structures.