Coarse-Grained Dynamics Assuming Equal-Probability for Transient States

Coarse Grained Molecular Dynamics

Coarse-grained protein molecular dynamics simulations.

A limiting factor in biological science is the time-scale gap between experimental and computational trajectories. At this point, all-atom explicit solvent molecular dynamics (MD) are clearly too expensive to explore long-range protein motions and extract accurate thermodynamics of proteins in isolated or multimeric forms. To reach the appropriate time scale, we must then resort to coarse grain...

Coarse-grained molecular dynamics simulations of biomolecules

Coarse-grained molecular dynamics (CGMD) simulations are increasingly being used to analyze the behaviors of biological systems. When appropriately used, CGMD can simulate the behaviors of molecular systems several hundred times faster than elaborate all-atom molecular dynamics simulations with similar accuracy. CGMD parameters for lipids, proteins, nucleic acids, and some artificial substances...

Coarse-Grained Modeling of Protein Unfolding Dynamics

We present a new dynamic elastic network model (DENM) that describes the unfolding process of a force-loaded protein. The protein interaction network and its potentials are constructed based on information of its native-state structure obtained from the Protein Data Bank, with network nodes positioned at the Cα coordinates of the protein backbone. Specifically, to mimic the unfolding process, i...

Accuracy of coarse grained Markovian dynamics

Markov chain models on a mesoscopic level are a widely used description for complex systems. They are based on the assumption that certain sets of microstates can be coarse grained as their internal dynamics is faster than the time scales considered in themodeling. Here we analyze quantitatively the errors made by using lumping techniques and present the first rigorous proof for bounds on such ...