Recapturing the Correlated Motions of Protein Using Coarse- Grained Models

Long-range interactions and allostery are important for many biological processes. Increasing numbers of studies, both experimental and computational, show that internal dynamics may play an important role in such behaviors. Investigating the dynamical effects of proteins, how- ever, is a challenging problem using all-atom molecular dynamics because of the length-scales and timescales involved. As a result, coarse-grained models are often implemented. Herein, we use three well-defined coarse-grained models: Go, Martini and Cafemol, and a small model protein Eglin C, which is readily studied via all-atom molecular dynamics, to examine if these coarse grained models can explore the dynamics of Eglin C accurately as well as to see how these models respond to mutations. We found that all three models can recapture the dynamics of Eglin C to a significant extent - where we focus on root-mean square fluctuations and correlated motions as dynamical measures - but that the Cafemol and Go models are superior. The best agreement with all-atom simulations is for structured regions of Eglin C.