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Chemical Information Based Elastic Network Model: A Novel Way To Identification Of Vibration Frequencies In Proteins.

Abstract
A novel method of analysis of macromolecules has been worked upon through this research. In an effort to understand the dynamics of macromolecules and to further our knowledge, pertaining specifically to the low frequency domain and also to elucidate certain important biological functions associated with it, a theoretical technique of chemical information based Normal Mode Analysis has been developed. These simulations render users with the ability to generate animations of modeshapes as well as key insight on the associated vibration frequencies. Harmonic analysis using atomistic details is performed taking into account appropriate values of masses of constituent atoms of a given macromolecule. In order to substantiate the applicability of such a technique, simple linear molecules were first worked upon. Subsequently, this technique has been applied to relatively more complex structures like amino acids, namely Cysteine. Consequently, this approach was extended to large macromolecules like Lactoferrin. Animations of modeshapes from simulations suggest a one to one correspondence with other computational techniques reported by other researchers. Computed β-factors are also in close agreement with the experimentally observed values of the same. Hence, as opposed to a simple Cα coarse grained model, our method with right masses and reasonable force fields yields not only the correct modeshapes but also provides us with useful information on wavenumbers that can be used to extract useful information about the frequency domain. Moreover, as opposed to conventional Molecular Dynamics’ simulations and Laser spectroscopy, the proposed methodology is significantly faster, cheaper and efficient.
Type
open
article
thesis
Date
2009-01-01
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