We presented a feasible framework of studying dynamics of macromolecules by applying elastic network model (ENM) and vibration spectroscopy. We first identified the precise force constants of covalent bonds commonly observed in macromolecules by matching their reported Raman shifts data with predicted wavenumbers determined by normal mode analysis (NMA). Assigning the obtained spring constants to other small chemical compounds such as ethynyl isocyanide (C3HN) and diacetylene (C4H2), we not only predicted their vibration wavenumbers precisely but also identified their individual mode shapes from NMA. We extensively tested this chemical information based ENM with one of amino acids, cysteine. Subsequent comparison of frequencies and modeshapes also yields a strong agreement between computed and experimental data. Consequently, the proposed method enables us to identify low frequency modeshapes that are in general functionally important collective motions of macromolecules but have hardly been revealed experimentally even using terahertz spectroscopy.