Dynamic coarse-graining fills the gap between atomistic simulations and experimental investigations of mechanical unfolding

Abstract

We present a dynamic coarse-graining technique that allows one to simulate the mechanical unfolding of biomolecules or molecular complexes on experimentally relevant time scales. It is based on Markov state models (MSMs), which we construct from molecular dynamics simulations using the pulling coordinate as an order parameter. We obtain a sequence of MSMs as a function of the discretized pulling coordinate, and the pulling process is modeled by switching among the MSMs according to the protocol applied to unfold the complex. This way we cover seven orders of magnitude in pulling speed. In the region of rapid pulling, we additionally perform steered molecular dynamics simulations and find excellent agreement between the results of the fully atomistic and the dynamically coarse-grained simulations. Our technique allows the determination of the rates of mechanical unfolding in a dynamical range from approximately 10/ns to 1/ns thus reaching experimentally accessible time regimes without abandoning atomistic resolution.

Loss of Molecular Roughness upon Coarse-Graining Predicts the Artificially Accelerated Mobility of Coarse-Grained Molecular Simulation Models

“…Some effort has been directed toward the development of dynamic CG models − that accurately describe dynamical properties, such as the diffusion coefficient, by including them as targets in the parametrization, thus enforcing correct dynamical behavior within the coarse-graining process. Our own experience shows that, very often, this has the undesirable side effect of worsening the reproduction of other structural or thermodynamic properties.…”

Coarse-Grained Models of RNA Nanotubes for Large Time Scale Studies in Biomedical Applications

“…This reveals that it is possible to efficiently manipulate such properties and characteristics for larger size RNA nanotubes, which are practically important for drug delivery and other biomedical applications of these structures. The developed models could be further generalized to account for more complex multiscale interactions, integrating our developed methodology with predictive, dynamic, and stochastic coarse-grained approaches [11,[57][58][59][60][61][62]. This would allow us to better face challenges of a vast separation of spatial and temporal scales between processes happening at the atomic and cellular levels and to provide a route for more efficient integrations of atomistic and molecular information into larger-scale models.…”

Non-equilibrium Markov state modeling of periodically driven biomolecules

“…Our strategy is different. From stationary atomistic MD simulations, and using standard tools, we construct a series of N equilibrium Markov state models parametrized by the value of the external parameter λ [20]. The procedure is sketched in Fig.…”

“…Here we develop a method to systematically construct periodically driven coarse-grained MSMs from atomistic data. To this end, we combine previous work on nonequilibrium Markov state modeling (NE-MSM) for timedependent protocols [20] and non-equilibrium steady states [10,21]. Specifically, we construct a series of equilibrium fine-grained MSMs at different values of the external parameter.…”