Application of elastic network models to proteins in the crystalline state.
Normal mode analysis using elastic network models has grown popular for probing the low-frequency collective dynamics of proteins and other biomolecular assemblies. In most previous studies, these models were validated by comparing calculated atomic fluctuations for isolated proteins with experimental temperature factors determined in the crystalline state, although there were also hints that including crystal contacts in the calculations has an impact on the comparison. In this study, a set of 83 ultra-high resolution crystal structures with experimentally determined anisotropic displacement parameters is used to evaluate several C(alpha)-based elastic network models that either ignore or treat the crystal environment in different ways; the latter include using periodic boundary conditions defined with respect to the asymmetric unit or the primitive unit cell as well as using the Born-von Kármán boundary condition that accounts for lattice vibrations. For all elastic network models, treating the crystal environment leads to better agreement with experimental anisotropic displacement parameters with the Born-von Kármán boundary condition giving the best agreement. Atomic correlations over the entire protein are clearly affected by the presence of the crystal contacts and fairly sensitive to the way that the crystal environment is treated. These observations highlight the importance of properly treating the protein system in an environment consistent with experiment when either evaluating approximate protein models or using approximate dynamic models in structural refinement application types. Finally, investigation of the scaling behaviors of the cumulative density of states and the heat capacity indicates that there are still gaps between simplified elastic models and all-atom models for proteins.
Riccardi
Demian
D
Program of Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Cui
Qiang
Q
Phillips
George N
GN
D016880:Anisotropy; D003198:Computer Simulation; D003460:Crystallization; D004777:Environment; D006358:Hot Temperature; D008958:Models, Molecular; D015233:Models, Statistical; D016571:Neural Networks, Computer; D011506:Proteins / Q000737:chemistry*; D053676:Syntenins / Q000737:chemistry; D013696:Temperature; D014961:X-Ray Diffraction / Q000379:methods
D011506:Proteins; D053676:Syntenins