4.7 Article

Enhanced sampling using replica exchange with nonequilibrium switches: A case study on simple models

Journal

JOURNAL OF CHEMICAL PHYSICS
Volume 157, Issue 18, Pages -

Publisher

AIP Publishing
DOI: 10.1063/5.0110826

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RENS is a computational technique that achieves extensive configurational sampling from a sequence of equilibrium and nonequilibrium MD simulations without modifying the potential energy surface. Unlike REMD, RENS uses nonequilibrium heating and cooling simulations to improve acceptance probability with only a few replicas.
Configurational sampling is central to characterize the equilibrium properties of complex molecular systems, but it remains a significant computational challenge. The conventional molecular dynamics (MD) simulations of limited duration often result in inadequate sampling and thus inaccurate equilibrium estimates. Replica exchange with nonequilibrium switches (RENS) is a collective variable-free computational technique to achieve extensive sampling from a sequence of equilibrium and nonequilibrium MD simulations without modifying the underlying potential energy surface of the system. Unlike the conventional replica exchange molecular dynamics (REMD) simulation, which demands a significant number of replicas for better accuracy, RENS employs nonequilibrium heating (forward) and cooling (reverse) work simulations prior to configurational swaps to improve the acceptance probability for replica exchange by using only a few replicas. Here, we have implemented the RENS algorithm on four model systems and examined its performance against the conventional MD and REMD simulations. The desired equilibrium distributions were generated by RENS for all the model systems, whereas REMD and MD simulations could not do so due to inadequate sampling on the same timescales. The calculated work distributions from RENS obeyed the expected nonequilibrium fluctuation theorem. The results indicate that the switching time of the nonequilibrium simulations can be systematically altered to optimize the acceptance probability and the reduced work of switching. The modular implementation of RENS algorithm not only enables us to readily extend it to multiple replicas but also paves the way for extension to larger molecular systems in the future.

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