(63c) Accurate Calculations of Partition Coefficients (Log POW and Log PMW) with Atomistic Simulation Methods | AIChE

(63c) Accurate Calculations of Partition Coefficients (Log POW and Log PMW) with Atomistic Simulation Methods

Authors 

Reith, D. - Presenter, Bonn-Rhein-Sieg University of Applied Sciences
Arnold, A. W., Fraunhofer Institute for Algorithms and Scientific Computing (SCAI)
Köddermann, T., Fraunhofer Institute for Algorithms and Scientific Computing (SCAI)

Octanol/water and membrane/water partition coefficients of a substance measure its solubility in octanol/membrane compared to water. They can be seen as simple models for its solubility in biological membranes, which ultimately is a rough estimate for toxicity. If a substance is hardly soluble in octanol, it is practically impossible for it to enter (human) cells, and therefore is less likely to be toxic. On the other hand, for novel drugs it might be important to penetrate the cell through the membrane, or even integrate into it. While for simple substances the log POW is concentration-independent, this is not true for ionic liquids. Being able to determine log POW values a priori from molecular dynamics simulations is an important step in virtual material design. To do so, we firstly present our methods to semi-automatically derive robust and reliable force field parameters for soft matter components. Secondly, we present a method to accurately calculate log POW values from atomistic computer simulations, even for substances with concentration-dependent log POW . Our method is based on the calculation of solvation free energies in water and octanol using thermodynamic integration. By way of using a simple association-dissociation model for the concentration dependence of the chemical potentials, we were able to reproduce concentration-dependent log POW values for a commonly used ionic liquids like [CnMIM][NTf2], [N1888][NTf2], and [P666(16)][NTf2]. Additionally we present results for simulated Log PMW values of these ILs generated with the umbrella sampling technique.

References:

[1] M. Hülsmann, T. Köddermann, J. Vrabec, and D. Reith: “GROW: A Gradient-based optimisation workflow for the automated development of molecular models”, Computer Physics Communications 181, 499–513 (2010). DOI:10.1016/j.cpc.2009.10.024

[2] T. Köddermann, D. Reith, and R. Ludwig, "Force Field comparison on various model approaches – how to design the best model for the ionic liquid family [CnMIM][NTf2]," Chem. Phys. Chem. 14, 3368-3374 (2013). DOI: 10.1002/cphc.201300486

[3] T. Köddermann, D. Reith, and A. Arnold, "Calculating concentration-dependent Log Pow values from Atomistic Computer Simulations," J. Chem. Phys. B ,117, 10711-10718 (2013). DOI: 10.1021/jp405383f

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