## Multiscale Macromolecular Simulation: Role of Evolving Ensembles

journal contribution

posted on 22.10.2012, 00:00 by A. Singharoy, H. Joshi, P. J. OrtolevaMultiscale analysis provides an algorithm for the efficient
simulation
of macromolecular assemblies. This algorithm involves the coevolution
of a quasiequilibrium probability density of atomic configurations
and the Langevin dynamics of spatial coarse-grained variables denoted
order parameters (OPs) characterizing nanoscale system features. In
practice, implementation of the probability density involves the generation
of constant OP ensembles of atomic configurations. Such ensembles
are used to construct thermal forces and diffusion factors that mediate
the stochastic OP dynamics. Generation of all-atom ensembles at every
Langevin time step is computationally expensive. Here, multiscale
computation for macromolecular systems is made more efficient by a
method that self-consistently folds in ensembles of all-atom configurations
constructed in an earlier step, history, of the Langevin evolution.
This procedure accounts for the temporal evolution of these ensembles,
accurately providing thermal forces and diffusions. It is shown that
efficiency and accuracy of the OP-based simulations is increased via
the integration of this historical information. Accuracy improves
with the square root of the number of historical timesteps included
in the calculation. As a result, CPU usage can be decreased by a factor
of 3–8 without loss of accuracy. The algorithm is implemented
into our existing force-field based multiscale simulation platform
and demonstrated via the structural dynamics of viral capsomers.

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quasiequilibrium probability densityOP dynamicsLangevin evolutionsquare rootEnsemblesMultiscale analysisgenerationSuch ensemblesprobability densitymultiscale computationconfigurationmultiscale simulation platformprocedure accountsLangevin time stepOP ensemblesMultiscale Macromolecular SimulationLangevin dynamicsorder parametersCPU usageaccuracydiffusion factorsalgorithmnanoscale system features

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### Categories

### Keywords

quasiequilibrium probability densityOP dynamicsLangevin evolutionsquare rootEnsemblesMultiscale analysisgenerationSuch ensemblesprobability densitymultiscale computationconfigurationmultiscale simulation platformprocedure accountsLangevin time stepOP ensemblesMultiscale Macromolecular SimulationLangevin dynamicsorder parametersCPU usageaccuracydiffusion factorsalgorithmnanoscale system features