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Coarse-grained (CG) modeling has emerged as a promising tool to bridge the gap between the temporal and spatial scales of all-atom (AA) simulations and those of many important biological processes. Resolution exchange, a variant of the replica exchange method, combines the efficiency of CG simulation and the accuracy of AA simulation by swapping configurations between AA and CG simulations. The crucial step in a resolution exchange move is to rigorously reconstruct the high-resolution system from models at coarser resolutions. In this paper, configurational-bias Monte Carlo is adopted as a general method to rebuild the missing degrees of freedom rigorously for CG models and for the first time combined with resolution exchange. The new approach is demonstrated on an alkane and a peptide system. It is found that the efficiency of resolution exchange depends significantly on the quality of the CG model. [ABSTRACT FROM AUTHOR]

Annealed importance sampling assigns equilibrium weights to a nonequilibrium sample that was generated by a simulated annealing protocol [R. M. Neal, Stat. Comput. 11, 125 (2001)]. The weights may then be used to calculate equilibrium averages, and also serve as an “adiabatic signature” of the chosen cooling schedule. In this paper we demonstrate the method on the 50-atom dileucine peptide and an alanine 5-mer, showing that equilibrium distributions are attained for manageable cooling schedules. For dileucine, as naively implemented here, the method is modestly more efficient than constant temperature simulation. The alanine application demonstrates the success of the method when there is little overlap between the high (unfolded) and low (folded) temperature distributions. The method is worth considering whenever any simulated heating or cooling is performed (as is often done at the beginning of a simulation project or during a NMR structure calculation), as it is simple to implement and requires minimal additional computational expense. Furthermore, the naive implementation presented here can be improved. [ABSTRACT FROM AUTHOR]

We recently applied a multistage reweighting scheme to demonstrate the sampling of equilibrium configurational distributions of peptides from nonequilibrium, simulated annealing trajectories [E. Lyman and D. M. Zuckerman, J. Chem. Phys. 127, 065101 (2007)]. Here we demonstrate that a statistical variance reduction technique, resampling, improves the efficiency of the protocol by about a factor of 3 in a penta-alanine system. While we are not optimistic for the ultimate efficiency of purely temperature-based sampling methods, resampling-type improvements ought to find application in other (formally equivalent) nonequilibrium sampling protocols, such as Jarzynski-relation calculations and annealing-based NMR structure calculations. [ABSTRACT FROM AUTHOR]

Coarse-grained (CG) modeling has emerged as a promising tool to bridge the gap between the temporal and spatial scales of all-atom (AA) simulations and those of many important biological processes. Resolution exchange, a variant of the replica exchange method, combines the efficiency of CG simulation and the accuracy of AA simulation by swapping configurations between AA and CG simulations. The crucial step in a resolution exchange move is to rigorously reconstruct the high-resolution system from models at coarser resolutions. In this paper, configurational-bias Monte Carlo is adopted as a general method to rebuild the missing degrees of freedom rigorously for CG models and for the first time combined with resolution exchange. The new approach is demonstrated on an alkane and a peptide system. It is found that the efficiency of resolution exchange depends significantly on the quality of the CG model.