Elastic Network Models For Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses

Elastic network models (ENMs) have over the last decade enjoyed considerable success in the study of macromolecular dynamics. These models have been used to predict the global dynamics of a variety of proteins and protein complexes, ranging in size from single enzymes to macromolecular machines (Keskin et al. 2002), ribosomes (Tama et al. 2003, Wang et al. 2004) and viral capsids (Tama & Brooks, 2002, Tama & Brooks, 2005, Rader et al. 2005). They have provided insights into a wide range of protein behaviors, such as mechanisms of allosteric regulation (Ming & Wall, 2005, Bahar et al. 2007, Chennubhotla et al. 2008), protein-protein binding (Tobi and Bahar 2005), anisotropic response to uniaxial tension and unfolding (Eyal and Bahar, 2008, Sulkowska et al. 2008), colocalization of catalytic sites and key mechanical sites (e.g., hinges) (Yang & Bahar 2005), interactions at the binding sites (Ming & Wall, 2006), and energetics (Miller et al. 2008), to name a few. ENMs allow the global motions of a molecule to be quickly calculated, making them an ideal complement to conventional molecular dynamics (MD) simulations. Increasingly, variants of ENMs are being applied to non-equilibrium situations, such as the prediction of transition pathways between functional states separated by low energy barriers (Zheng et al. 2007) or driving MD simulations (Isin et al. 2008). At its core, the ENM provides a simplified representation of the potential energy function of a system, in this case a macromolecule or macromolecular