Nuclear Science and Techniques

《核技术》(英文版) ISSN 1001-8042 CN 31-1559/TL     2019 Impact factor 1.556

Nuclear Science and Techniques ›› 2013, Vol. 24 ›› Issue (3): 030201 doi: 10.13538/j.1001-8042/nst.2013.03.005


Statistical method for predicting protein absorption peaks in terahertz region

WU Yuting1  ZHANG Wenmei1  ZHAO Hongwei2  SHAO Zhifeng3  LI Xiaowei3   

  1. 1Institute of Modern Communication Technology, School of Physics and Electronics Engineering, Shanxi University, Taiyuan 030006, China
    2Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Jiading Campus, Shanghai 201800, China
    3Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine of Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2012-11-27
  • Contact: LI Xiaowei E-mail:
  • Supported by:

    Supported by National Science Foundation of China (Nos. 60907044, 91027020 and 11005148)

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WU Yuting, ZHANG Wenmei, ZHAO Hongwei, SHAO Zhifeng, LI Xiaowei. Statistical method for predicting protein absorption peaks in terahertz region.Nuclear Science and Techniques, 2013, 24(3): 030201     doi: 10.13538/j.1001-8042/nst.2013.03.005


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.


Key words: Terahertz, Molecular dynamics, Protein, Absorption spectrum