Application of coarse grained models to the analysis of macromolecular structures

Abstract

We review some of the computational methods that have been recently applied to the study of biological macromolecules, i.e. DNA, RNA, carbohydrates and proteins. The latter ones, in particular, have been the subject of intense studies aimed at understanding not only their equilibrium properties, but also their dynamics. However, in most cases of biological importance, the size of these molecules and the time scale on which they operate prevent from a direct application of all atoms techniques and demand the development of computationally efficient, yet physically sound, coarse grained models. We examine some recent advances in this field, and describe the Gaussian and Anisotropic Network Model, that have been recently applied to a variety of different proteins and nucleic acids. We finally show some preliminary results on the application of coarse grained models to the kinesin dimer.