Use of TSAR as a new tool to analyze the molecular dynamics trajectories of proteins

There is a lack of tools to analyze simulations of protein molecular dynamics quantitatively. Our aim is to use calmodulin, a prototypical calcium-binding protein, to describe a strategy and some tools for extracting relevant information from dynamics calculations. Our main conclusions are as follows: Autocorrelation vectors may be used to represent a 3D conformation in an n-dimensional space, where n is variable (n < or = 20-30). On such a transformation, classic statistical tools (PCA, clustering, etc.) may be used to differentiate or characterize dynamics trajectories quantitatively. TSAR, an integrated package used for quantitative structure-activity relationships, is well suited (after minor modifications) for such a purpose. Finally, this type of strategy is able to point out the effects of the solvent screening parameters of the Amber software on the dynamics trajectories of calmodulin.