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Thermal nanostructure: An order parameter multiscale ensemble approach

Source: J. Chem. Phys. 132, 075102 (2010); doi:10.1063/1.3316793

Published 19 February 2010

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ISSN:
1553-9644 (online)
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AIP is a member of CrossRef AIP
S. Cheluvaraja and P. Ortoleva
Department of Chemistry, Center for Cell and Virus Theory, Indiana University, Bloomington, Indiana 47405, USA
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 SIMNANOWORLDTM, 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. ©2010 American Institute of Physics
History: Received 13 October 2009; accepted 4 January 2010; published 19 February 2010
Permalink: http://link.aip.org/link/?JCPSA6/132/075102/1

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