Characterizing protein motions from structure
Journal of Molecular Graphics and Modelling
To clarify the extent structure plays in determining protein dynamics, a comparative study is made using three models that characterize native state dynamics of single domain proteins starting from known structures taken from four distinct SCOP classifications. A geometrical simulation using the Framework Rigidity Optimized Dynamics Algorithm (FRODA) based on rigid cluster decomposition is compared to the commonly employed elastic network model (specifically the Anisotropic Network Model ANM)
... d molecular dynamics (MD) simulation. The essential dynamics are quantified by a mode subspace constructed from ANM and a principal component analysis (PCA) on FRODA and MD trajectories. Aggregate conformational ensembles are constructed to provide a basis for quantitative comparisons between FRODA runs using different parameter settings to critically assess how the predictions of essential dynamics depend on a priori arbitrary user-defined distance constraint rules. We established a range of physicality for these parameters. Surprisingly, FRODA maintains greater intra-consistent results than obtained from MD trajectories, comparable to ANM. Additionally, a mode subspace is constructed from PCA on an exemplar set of myoglobin structures from the Protein Data Bank. Significant overlap across the three model subspaces and the experimentally derived subspace is found. While FRODA provides the most robust sampling and characterization of the native basin, all three models give similar dynamical information of a native state, further demonstrating that structure is the key determinant of dynamics. Methods Anisotropic Network Model (ANM) ANM calculations were done using the Anisotropic Network Model web server: All runs were performed online at http://ignmtest.ccbb.pitt.edu/cgi-bin/anm/ Each analysis used a distance cutoff of 15 Å and a weighted C-C distance of 2.5 Å. Molecular Dynamics (MD) MD trajectories were downloaded  from www.Dynameomics.org The methodology used to generate the trajectories is available at the same URL.