A unification of the elastic network model and the gaussian network model for optimal description of protein conformational motions and fluctuations

Coarse-grained elastic models with a C_α-only representation and harmonic interactions have been increasingly used to describe the conformational motions and flexibility of various proteins. In this work, we will unify two complementary elastic models-the elastic network model (ENM) and the Gaussian network model (GNM), in the framework of a generalized anisotropic network model (G-ANM) with a new anisotropy parameter, f _anm. The G-ANM is reduced to GNM at f_anm = 1, and ENM at f_anm = 0. By analyzing a list of protein crystal structure pairs using G-ANM, we have attained optimal descriptions of both the isotropic thermal fluctuations and the crystallographically observed conformational changes with a small f_anm (f_anm ≤ 0.1) and a physically realistic cutoff distance, R_c ∼ 8Å. Thus, the G-ANM improves the performance of GNM and ENM while preserving their simplicity. The properly parameterized G-ANM will enable more accurate and realistic modeling of protein conformational motions and flexibility.