A Study of Conformational Changes in Macromolecules: The Coarse-grained Elastic Network Interpolation Method

It is well known that the structure of a biological molecule is strongly related to its function. Many researchers have investigated the relationship between structure and function. As the structural information of macromolecules can be obtained from experimental methods such as NMR and X-ray crystallography at atomic detail, computational methods such as molecular dynamics (MD) and normal mode analysis (NMA) are used for inferring conformational changes and functions from structures. In this paper, we discuss a coarse-grained elastic network interpolation method (ENI) which is faster than MD and is able to generate feasible pathways. Coarse-grained ENI uses only the C _α, of each residue in a protein to produce a reduced degree-of-freedom (DOF) model in which interactions are modelled with Gaussian/ harmonic potentials. The key idea is to generate intermediate conformations by interpolating the distances between atoms. This method is tested for several proteins which have large-scale motions during transitions as well as a viral capsid maturation process and an RNA conformational change. In addition, coarse-grained ENI results for this RNA are quantitatively compared with those of MD simulation. These results may serve as a new paradigm for reduced DOF dynamic simulations of large biological molecules as well as a method for the reduced-parameter interpretation of massive amounts of MD data.