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Configurational Bias Monte Carlo of Molecules in Solvent and Comparison with Molecular Dynamics

Henrique Musseli Cezar (Institute of Physics, University of São Paulo, Brazil)
Sylvio Canuto (Institute of Physics, University of São Paulo, Brazil)
Kaline Coutinho (Institute of Physics, University of São Paulo, Brazil)

The molecular structure plays an important role in several processes in
physics, chemistry and biology. Computationally, to identify the structures and
sample the configurations in a desired ensemble, typically either Molecular
Dynamics (MD) or Monte Carlo (MC) simulation is used. Depending on which
properties one is interested in obtaining, or the molecule to be studied; one
method may be more suitable than the other. However, MC lacks a standard and
established method to sample the molecular internal degrees of freedom of a
molecule, since the atomic displacements usually applied within the method are
very inefficient to generate large conformational changes. The goal of this
work was to implement and improve a Configurational Bias Monte Carlo (CBMC)
method able to efficiently sample molecular conformations of molecules in
solvent. Based on the work of Shah and Maginn [1,2] we implemented in the DICE
package [3] an algorithm that breaks the molecule into smaller fragments,
separating hard and soft degrees of freedom and reconnect those fragments
generating new configurations. The proposed acceptance criteria for those
movements are shown to satisfy the detailed balance. Therefore, the sampling of
the correct ensemble is guaranteed. After the implementation [4] we did our
first applications in well-known systems to study their flexibility in
solution. They are: octane and 1,2-dicholoroethane in different solvents.
Additionally we compared the trans and gauche populations with experimental
data and results from MD simulations. In both cases the results had an
excellent agreement. We verify that at least for those systems, our CBMC
implementation achieves the correct populations faster than MD and is less
likely to get trapped in local minima.

[1] J. K. Shah, E. J. Maginn J. Chem. Phys. 2011, 135(13), 134121.
[2] J. K. Shah, E. Marin-Rimoldi, R. G. Mullen, B. P. Keene, S. Khan, A. S. Paluch, N. Rai, L. L. Romanielo, T. W. Rosch, B. Yoo, E. J. Maginn. J. Comput. Chem. 2017, DOI: 10.1002/jcc.24807.
[3] K. Coutinho, S. Canuto, DICE: A Monte Carlo Program for Molecular Liquid Simulation, v: 2.9; University of São Paulo: Brazil, 2011.
[4] H. M. Cezar, S. Canuto, K. Coutinho (manuscript in preparation)

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