ArticleThe Journal of chemical physics2010
Thermal nanostructure: an order parameter multiscale ensemble approach.
Article in The Journal of chemical physics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 26 citations in OpenAlex.
- Enhanced Sampling of an Atomic Model with Hybrid Nonequilibrium Molecular Dynamics-Monte Carlo Simulations Guided by a Coarse-Grained Model.Journal of chemical theory and computation · 2015Article
- Multiscale Factorization Method for Simulating Mesoscopic Systems with Atomic Precision.Journal of chemical theory and computation · 2014Article
- Article
- Multiscale macromolecular simulation: role of evolving ensembles.Journal of chemical information and modeling · 2012Article
- Space warping order parameters and symmetry: application to multiscale simulation of macromolecular assemblies.The journal of physical chemistry. B · 2012Article
- Discovering free energy basins for macromolecular systems via guided multiscale simulation.The journal of physical chemistry. B · 2012Article
- Hierarchical Order Parameters for Macromolecular Assembly Simulations I: Construction and Dynamical Properties of Order Parameters.Journal of chemical theory and computation · 2012Article
- Multiscale simulation of microbe structure and dynamics.Progress in biophysics and molecular biology · 2011Article
- The coat protein leads the way: an update on basic and applied studies with the Brome mosaic virus coat protein.Molecular plant pathology · 2011Review
- Order parameters for macromolecules: application to multiscale simulation.The Journal of chemical physics · 2011Article
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Authors and funding
2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Deductive all-atom multiscale techniques imply that many nanosystems can be understood in terms of the slow dynamics of order parameters that coevolve with the quasiequilibrium probability density for rapidly fluctuating atomic configurations. The result of this multiscale analysis is a set of stochastic equations for the order parameters whose dynamics is driven by thermal-average forces. We present an efficient algorithm for sampling atomistic configurations in viruses and other supramillion atom nanosystems. This algorithm allows for sampling of a wide range of configurations without creating an excess of high-energy, improbable ones. It is implemented and used to calculate thermal-average forces. These forces are then used to search the free-energy landscape of a nanosystem for deep minima. The methodology is applied to thermal structures of Cowpea chlorotic mottle virus capsid. The method has wide applicability to other nanosystems whose properties are described by the CHARMM or other interatomic force field. Our implementation, denoted SIMNANOWORLD, achieves calibration-free nanosystem modeling. Essential atomic-scale detail is preserved via a quasiequilibrium probability density while overall character is provided via predicted values of order parameters. Applications from virology to the computer-aided design of nanocapsules for delivery of therapeutic agents and of vaccines for nonenveloped viruses are envisioned.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.