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Terahertz vibrational spectroscopy has recently been demonstrated as a novel noninvasive technique for the characterization of biological molecules. But the interpretation of the experimentally measured terahertz absorption bands requires robust computational method. In this paper, we present a statistical method for predicting the absorption peak positions of a macromolecule in the terahertz region. The essence of this method is to calculate the absorption spectra of a biological molecule based on multiple short scale molecular dynamics trajectories instead of using a long time scale trajectory. The method was employed to calculate the absorption peak positions of the protein, thioredoxin from Escherichia coli (E.coli), in the range of 10-25 cm -1 to verify the reliability of this statistical method. The predicted absorption peak positions of thioredoxin show good correlation with measured results demonstrating that the proposed method is effective in terahertz absorption spectra modeling. Such approach can be applied to predict characteristic spectral features of biomolecules in the terahertz region.
Terahertz vibrational spectroscopy has recently been demonstrated as a novel noninvasive technique for the characterization of biological molecules. But the interpretation of the experimentally measured terahertz absorption bands requires robust computational method. In this paper, we present a statistical method for predicting the absorption peak positions of The essence of this method is to calculate the absorption spectra of a biological molecule based on multiple short scale molecular dynamics trajectories instead of using a long time scale trajectory. The method was employed to calculate the absorption peak positions of the protein, thioredoxin from Escherichia coli (E. coli), in the range of 10-25 cm -1 to verify the reliability of this statistical method. The predicted absorption peak positions of thioredoxin show good correlation with measured results demonstrating that the proposed method is effective in terahertz absorption spectra mode This approach can be applied to predict characteristic spectral features of biomolecules in the terahertz region.