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  Enabling grand-canonical Monte Carlo: Extending the flexibility of GROMACS through the GromPy python interface module.

Pool, R., Heringa, J., Höfling, M., Schulz, R., Smith, J. C., & Feenstra, K. A. (2012). Enabling grand-canonical Monte Carlo: Extending the flexibility of GROMACS through the GromPy python interface module. Journal of Computational Chemistry, 33(12), 1207-1214. doi:10.1002/jcc.22947.

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Pool, R., Author
Heringa, J., Author
Höfling, M.1, Author           
Schulz, R., Author
Smith, J. C., Author
Feenstra, K. A., Author
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1Department of Theoretical and Computational Biophysics, MPI for biophysical chemistry, Max Planck Society, ou_578631              

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Free keywords: grand-canonical Monte Carlo; GROMACS; python; API; trajectory analysis
 Abstract: We report on a python interface to the GROMACS molecular simulation package, GromPy (available at https://github.com/GromPy). This application programming interface (API) uses the ctypes python module that allows function calls to shared libraries, for example, written in C. To the best of our knowledge, this is the first reported interface to the GROMACS library that uses direct library calls. GromPy can be used for extending the current GROMACS simulation and analysis modes. In this work, we demonstrate that the interface enables hybrid Monte-Carlo/molecular dynamics (MD) simulations in the grand-canonical ensemble, a simulation mode that is currently not implemented in GROMACS. For this application, the interplay between GromPy and GROMACS requires only minor modifications of the GROMACS source code, not affecting the operation, efficiency, and performance of the GROMACS applications. We validate the grand-canonical application against MD in the canonical ensemble by comparison of equations of state. The results of the grand-canonical simulations are in complete agreement with MD in the canonical ensemble. The python overhead of the grand-canonical scheme is only minimal.

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Language(s): eng - English
 Dates: 2012-02-282012-05-05
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1002/jcc.22947
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Title: Journal of Computational Chemistry
Source Genre: Journal
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Pages: - Volume / Issue: 33 (12) Sequence Number: - Start / End Page: 1207 - 1214 Identifier: -