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g_permute: Permutation-reduced phase space density compaction.

MPS-Authors
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Lange,  O.F.
Department of Theoretical and Computational Biophysics, MPI for biophysical chemistry, Max Planck Society;

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Haas,  J.
Department of Theoretical and Computational Biophysics, MPI for biophysical chemistry, Max Planck Society;

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Grubmüller,  H.
Department of Theoretical and Computational Biophysics, MPI for biophysical chemistry, Max Planck Society;

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Citation

Reinhard, F., Lange, O., Hub, J., Haas, J., & Grubmüller, H. (2009). g_permute: Permutation-reduced phase space density compaction. Computer Physics Communications, 180(3), 455-458. doi:10.1016/j.cpc.2008.10.018.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0027-C073-2
Abstract
Biomolecular processes are governed by free energy changes and thus depend on a fine-tuned interplay between entropy and enthalpy. To calculate accurate values for entropies from simulations is particularly challenging for the solvation shell of proteins, which contributes crucially to the total entropy of solvated proteins, due to the diffusive motion of the solvent molecules. Accordingly, for each frame of a Molecular dynamics (MD) trajectory, our software relabels the solvent molecules, such that the resulting configuration space volume is reduced by a factor of N! with N being the number of solvent molecules. The combinatorial explosion of a naive implementation is here overcome by transforming the task into a linear assignment problem, for which algorithms with complexity O(N3)O(N3) exist. We have shown in previous research that the solvent entropy can be estimated from such a compacted trajectory by established entropy estimation methods. In this paper, we describe the software implementation which also allows applications beyond entropy estimation, such as the permutation of lipids in membrane bilayers.