Protein structure analysis using the resonant recognition model and wavelet transforms.
An approach based on the resonant recognition model and the discrete wavelet transform is introduced here for characterising proteins' biological function. The protein sequence is converted into a numerical series by assigning the electron-ion interaction potential to each amino acid from N-terminal to C-terminal. A set of peaks is found after performing a wavelet transform onto a numerical series representing a group of homologous proteins. These peaks are related to protein structural and functional properties and named characteristic vector of that protein group. Further more, the amino acids contributing mostly to a protein's biological functions, the so-called 'hot spots' amino acids, are predicted by the continuous wavelet transform. It is found that the hot spots are clustered around the protein's cleft structure. The wavelets approach provides a novel methods for amino acid sequence analysis as well as an expansion for the newly established macromolecular interaction model: the resonant recognition model.
Department of Electrical and Computer System Engineering Monash University, Caulfield East Vic.
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Fang
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Cosic
D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D000818:Animals; D004563:Electrochemistry; D046911:Macromolecular Substances; D008958:Models, Molecular; D011487:Protein Conformation
D000596:Amino Acids; D046911:Macromolecular Substances