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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(alpha)-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) < or = 0.1) and a physically realistic cutoff distance, R(c) approximately 8 A. 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.