An efficient null model for conformational fluctuations in proteins

Abstract

Protein dynamics play a crucial role in function, catalytic activity, and pathogenesis. Consequently, there is great interest in computational methods that probe the conformational fluctuations of a protein. However, molecular dynamics simulations are computationally costly and therefore are often limited to comparatively short timescales. TYPHON is a probabilistic method to explore the conformational space of proteins under the guidance of a sophisticated probabilistic model of local structure and a given set of restraints that represent nonlocal interactions, such as hydrogen bonds or disulfide bridges. The choice of the restraints themselves is heuristic, but the resulting probabilistic model is well-defined and rigorous. Conceptually, TYPHON constitutes a null model of conformational fluctuations under a given set of restraints. We demonstrate that TYPHON can provide information on conformational fluctuations that is in correspondence with experimental measurements. TYPHON provides a flexible, yet computationally efficient, method to explore possible conformational fluctuations in proteins.