Title :
Investigation of the applicability of dielectric relaxation properties of amino acid solutions within the resonant recognition model
Author :
Pirogova, Elena ; Simon, George P. ; Cosic, Irena
Author_Institution :
Sch. of Electr. & Comput. Eng., RMIT Univ., Melbourne, Vic., Australia
fDate :
6/1/2003 12:00:00 AM
Abstract :
The resonant recognition model (RRM) is a physicomathematical approach used to analyze the interactions of a protein and its target, using digital signal processing methods. The RRM is based on the finding that there is a significant correlation between the spectra of numerical presentation of protein sequences and their biological activities. Initially, the electron-ion interaction potential was used to represent each amino acid in the protein sequences. In this paper, the dielectric constant (ε´) and dielectric loss tangent (tan δ) parameters have been determined for their possible use in the RRM. These parameters are based on the values of capacitance and conductance obtained experimentally for 20 amino acid solutions using dielectric spectroscopy for the case of the real component of dielectric permittivity; the parameter used is the dielectric increment (Δε´), the difference between dielectric constant of the amino acid solution and that of the solvent alone. The results of multiple cross-spectral analyses have shown that parameters analyzed generate in the consensus spectrum one dominant peak corresponding to the common biological activity of proteins studied, allowing the conclusion that these new parameters are suitable for use in the RRM approach.
Keywords :
bioelectric phenomena; capacitance; dielectric relaxation; molecular biophysics; organic compounds; permittivity; physiological models; proteins; resonance; amino acid solutions; biological activities; common biological activity; consensus spectrum; cross-spectral analyses; dielectric loss tangent; dielectric relaxation properties; digital signal processing methods; dominant peak; electron-ion interaction potential; physicomathematical approach; protein sequences; resonant recognition model; Amino acids; Biological system modeling; Charge carrier processes; Dielectric constant; Dielectric losses; Digital signal processing; Proteins; Resonance; Signal analysis; Target recognition; Amino Acid Sequence; Amino Acids; Binding Sites; Complex Mixtures; Electric Capacitance; Electric Conductivity; Electrochemistry; Feasibility Studies; Microchemistry; Models, Chemical; Molecular Sequence Data; Pattern Recognition, Automated; Protein Binding; Protein Interaction Mapping; Proteins; Sequence Analysis, Protein; Solutions; Structure-Activity Relationship;
Journal_Title :
NanoBioscience, IEEE Transactions on
DOI :
10.1109/TNB.2003.813936