Multiscale enhanced sampling driven by multiple coarse-grained models

Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

doi:10.1016/j.cplett.2014.10.009

Cited by 15 publications

(13 citation statements)

References 28 publications

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“…At variance with TAMD equations ( 3 ), the system equation ( 13 ) contains also a force on the z variables coming from a potential energy acting on these variables, V CV ( z ) [a version of MSES using multiple and mutually interacting z sets was presented in Moritsugu et al ( 2014b )]. This potential is arbitrarily chosen based on prior knowledge or experimental information.…”

Section: Methods To Explore and Reconstruct The Free-energy Landscapementioning

confidence: 99%

Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review

Fujisaki

Moritsugu

Matsunaga

et al. 2015

Front. Bioeng. Biotechnol.

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Molecular Dynamics simulations are a powerful approach to study biomolecular conformational changes or protein–ligand, protein–protein, and protein–DNA/RNA interactions. Straightforward applications, however, are often hampered by incomplete sampling, since in a typical simulated trajectory the system will spend most of its time trapped by high energy barriers in restricted regions of the configuration space. Over the years, several techniques have been designed to overcome this problem and enhance space sampling. Here, we review a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study. In particular, we illustrate the Temperature Accelerated Molecular Dynamics (TAMD), Logarithmic Mean Force Dynamics (LogMFD), and Multiscale Enhanced Sampling (MSES) algorithms. We also discuss combinations with techniques for searching reaction paths. We show the advantages presented by this approach and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.

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Section: Methods To Explore and Reconstruct The Free-energy Landscapementioning

confidence: 99%

Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review

Fujisaki

Moritsugu

Matsunaga

et al. 2015

Front. Bioeng. Biotechnol.

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“…We here compare our sampling efficiencies with those by the Multi-Scale Enhanced Sampling (MSES) [31,32] together with the Hamiltonian Replica Exchange Method (HEREM) [33]. As the computational cost to draw the folding FEL by MSES, several hundreds ns simulations (six replicas × 100 ns HREM simulations) were required.…”

Section: Validations Of the Conformational Sampling By Tbsamentioning

confidence: 99%

Efficient conformational sampling of proteins based on a multi-dimensional TaBoo SeArch algorithm: An application to folding of chignolin in explicit solvent

Harada

Takano

Shigeta

2015

Chemical Physics Letters

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“…Recently, Moritsugu et al [ 59 , 60 ] introduced ‘multiscale essential sampling’ (MSES), in which a protein system was expressed by an all-atom model, coupled with a coarse-grained model(s) to enhance conformational sampling. MSES was applied to protein–protein binding of a barnase–barstar system [ 61 ].…”

Section: Virtual-system Couplingmentioning

confidence: 99%

Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation

Iida

Nakamura

Higo

2016

Biochemical Journal

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We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein–protein or protein–ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks.

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Multiscale enhanced sampling driven by multiple coarse-grained models

Cited by 15 publications

References 28 publications

Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review

Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review

Efficient conformational sampling of proteins based on a multi-dimensional TaBoo SeArch algorithm: An application to folding of chignolin in explicit solvent

Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation

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