Generalized-ensemble algorithms for molecular simulations of biopolymers.

By Ayori Mitsutake, Y. Sugita, Y. O. I. F. M. Science, the Graduate University of the Advanced Studies. Biopolymers, 2000

698 citations recorded by the source corpus.

In complex systems with many degrees of freedom such as peptides and proteins, there exists a huge number of local-minimum-energy states. Conventional simulations in the canonical ensemble are of little use, because they tend to get trapped in states of these energy local minima. A simulation in generalized ensemble performs a random walk in potential energy space and can overcome this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review uses of the generalized-ensemble algorithms in biomolecular systems. Three well-known methods, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present three new generalized-ensemble algorithms that combine the merits of the above methods. The effectiveness of the methods for molecular simulations in the protein folding problem is tested with short peptide systems.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/2baae28c366cb2b3d10f3851324da8677c72d682

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Citations in the corpus

An overview of the Amber biomolecular simulation package (2013, methodology): “In Amber, REMD can now be used with either temperature or different Hamiltonians as the choice for independent variables, with recent modiﬁ-cations allowing both single-dimension and multiple-dimension REMD.”
Force fields for protein simulations. (2003, result): “…their backbone torsion angle behavior) by carrying out converged or nearly converged simulations on short peptides and comparing the resulting conformational populations to those derived from experiment (Damm and van Gunsteren, 2000; Mitsutake et al., 2001; Garcı́a and Sanbonmatsu, 2001).”
Enhanced Sampling Methods for Molecular Dynamics Simulations [Article v1.0] (2022, background): “exchange methods A broad category of simulation methodologies known as generalized ensemble [244] (also sometimes referred to extended ensemble [245]) algorithms have become popular over the last two decades.”
Weighted Ensemble Simulation: Review of Methodology, Applications, and Software (2017, neutral): “Thus, in contrast to other approaches for accessing long-timescale motions such as metadynamics (43), accelerated MD (34), and replica exchange (35, 47), path sampling approaches enable rigorous, straightforward calculations of rate constants without additional assumptions.”
Biological and synthetic membranes: What can be learned from a coarse-grained description? (2006, methodology): “Sometimes replica-exchange Monte Carlo, or parallel tempering methods, are employed [88–91].”