Micelle/water partition: A combination of molecular dynamics simulations and COSMOmic
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1 Micelle/water partition: A combination of molecular dynamics simulations and COSMOmic D. Yordanova, I. Smirnova, S. Jakobtorweihen Institute of Thermal Separation Processes, Hamburg University of Technology
2 Introduction Micelles aggregates of amphiphilic molecules (surfactants) Can solubilize hydrophobic compounds Used in separation processes Hydrophilic head Hydrophobic tail Hydrophobic solute Aqueous solution P i c Micelle i Water i c Decisive parameter regarding the selectivity and efficiency of micellar systems COSMOmic as potential screening tool Graphic: Amalgam Modelmaking Ltd 2
3 COSMOmic for micelles COSMOmic extension of COSMO-RS for anisotropic systems (membranes, micelles) Micelle structures radially divided into shells The last layer should contain only water Micelles assumed as spheres Layer thickness constant Different volume in each layer 3
4 Self-assembly MD simulation Micelle structures Input for COSMOmic Self-assembly a microscopic process Molecular dynamics (MD) simulations 216 surfactant monomers water molecules 50 ns 100 ns A random configuration Max micelle size 50 Max micelle size 180 4
5 Aims of the work Self-assembly MD simulations Suitable micelle structures for COSMOmic Prediction of partition coefficients of neutral solutes in micelle/water systems Influence of micelle structure (size and shape) on the prediction quality The same strategy for mixed micelle systems 5
6 Triton X-series Triton X-114, Triton X-100 Nonionic surfactants Triton X-114 mild extraction conditions Used in surfactant based extraction processes Membrane protein purifications n = 7-8 (Triton X-114) n = 9-10 (Triton X-100) Comparison with theoretical methods is of interest Influence of additives (ionic surfactants, salts) on the self-assembly process, micelle structure, partition behaviour of solutes Glembin et al., Sep. Purif. Technol. 2014, Safonova et al., Chem. Eng. Res. Des. 2014,
7 Methods MD simulations Force field the fundamental model behind every MD simulation Interaction model Describes the potential energy of a system of particles (molecules and atoms) V total = V intramolecular + V intermolecular V intermolecular = V van der Waals + V electrostatic Pastor and MacKerell, J. Phys. Chem. Lett. 2011, Klauda et al., J. Phys. Chem. B 2010, Vanommeslaeghe et al., J. Comput. Chem. 2009,
8 Parametrization of Triton X-molecules CHARMM36 additive force field CHARMM General Force Field (CGenFF) for drug-like molecules Limited data base Triton X-molecules not available Parametrization of the Triton X-molecules Hydrophobic part: 6 charges 1 bond 4 angles 8 dihedrals Hydrophilic part: 1 dihedral Yordanova et al., J. Chem. Theory Comput. 2015, submitted. 8
9 Input structure from self-assembly simulation Input for COSMOmic: micelle structure from a self-assembly simulation Snapshot (single micelle) Average atomic distributions [ Jakobtorweihen et al., J. Comput. Chem. 2013, ] More physically reasonable approach Reduces the effect of outliers Most probable micelle sizes, obtained in the MD simulations The atomic distributions were averaged over at least 200 micelles 9
10 Input structure from self-assembly simulation Storm et al. gaps in the water layer around some micelles, deriving from another micelle in close proximity worse prediction quality An approach to adjust the atomic distributions to the correct density Surfactant atoms not part of the micelle, are replaced by an equivalent amount of water Overcomes the effect of outliers, resulting from a deficient water layer around the micelle Storm et al., J. Phys. Chem. B 2014,
11 Input structures: pre-assembled micelles Pre-assembled micelles A single micelle with predetermined micelle size Built with Packmol Simulated in a water box for 40 ns Advantages: Smaller systems A single micelle in the box no gaps in the water shell Micelle size can be freely choosen Packmol: Martinez et al., J. Comput. Chem. 2009,
12 Prediction of partition coefficients in the systems Triton X-114/water and Triton X-100/water 12
13 Prediction of partition coefficients between Triton X-micelles and water Triton X-114/ water Aggregation number = 32 Triton X-100/ water Aggregation number = neutral solutes RMSE = neutral solutes RMSE = 0.32 RMSE 1 n n i1 log MW, COSMOmic P i log P MW,exp i 2 13
14 Prediction of partition coefficients between Triton X-micelles and water Triton X-114/ water Aggregation number = 32 Triton X-100/ water Aggregation number = neutral solutes RMSE = neutral solutes RMSE =
15 Prediction of partition coefficients Influence of size and shape COSMOmic assumes the micelle structure as sphere 0 - the micelle is perfect sphere Micelle geometry (size and shape) has an effect on the prediction quality Structures which show the most stable results are favored 15
16 Prediction of partition coefficients in mixed micellar systems 16
17 Prediction of partition coefficients in the system Triton X-114/SDS Most technically applicable micelle systems mixed micelles Influence of the anionic surfactant Sodium Dodecyl Sulfate (SDS) Self-assembled micelles Triton X-114 and SDS equimolar (100 ˣ Triton X-114, 100 ˣ SDS, ˣ Water, 100 ˣ Na Pre-assembled micelles Constant Triton X-114/SDS ratio Aggregation numbers 40, 50,
18 Prediction of partition coefficients in the system Triton X-114/SDS Self-assembled micelles No significant differences in the obtained aggregation numbers, eccentricities, RMSEs Pre-assembled micelles Worse prediction quality when using larger micelles (100) 18
19 Prediction of partition coefficients in the system Triton X-114/SDS Self-assembled micelle: Pre-assembled micelle: Aggregation number = 44 RMSE = neutral solutes Aggregation number = 40 RMSE = 0.32 RMSEs in mixed micelles in the same range as in the pure Triton X/water systems 19
20 Conclusions and outlook Micelle structures from MD simulations for both pure and mixed micelle systems Both self-assembled and pre-assembled micelles can be used as input for COSMOmic Small spherical micelles are recommended Prediction of partition coefficients An overall good agreement with experimental results for neutral solutes in both Triton X/water systems and in mixed micelle systems Future work Influence of other additives (cationic surfactants, salts) Prediction of partition coefficients of charged solutes Simulation of other nonionic surfactants 20
21 Acknowledgements: Thank you for your attention!
22 Cloud Point Extraction T > Cloud Point Temperature water-rich phase surfactant-rich phase 22
23 23
24 ParamChem Automation of the CGenFF Input: mol2 file (structure) Assignment of parameters by analogy Output: CHARMM toppar stream file Penalty the highest penalty score of the associated parameters Vanommeslaeghe and MacKerell, J. Chem. Inf. Model. 2012,
25 Parametrization workflow Structure Preparation (PSF/PDB files) Geometry optimization (QM) CHARGES Water Interaction Energy (QM) Charge optimization BONDS & ANGLES According to the CGenFF parametrization procedure MP2/6-31G(d) level of theory HF/6-31G(d) interactions with a TIP3P water molecule Hessian calculation (QM) Bond & Angle optimization DIHEDRALS Torsion Scans (QM) Dihedral optimization MP2/6-31G(d) Potential Energy Scans (PES) Force field Toolkit Plugin (fftk) Gaussian 03 Mayne et al., J. Comput. Chem. 2013,
26 Optimized dihedrals 8 dihedrals optimized in the hydrophobic part (1,1,3,3-tetramethyl-benzene) 1 dihedral optimized in ethylene glycol monomethyl ether Energy [kcal/mol] Energy [kcal/mol] Conformation Conformation RMSE = RMSE = Very good agreement with QM potential energy scans 26
27 Self-assembly simulations Critical micelle concentration (CMC) 0.17 mm (Triton X-114) 0.22 mm (Triton X-100) Much higher concentrations in the simulations Surfactant Surfactant molecules Water molecules Total number of atoms Csurf [mol/l] T [K] Simulation time [ns] TX TX TX TX Very large systems Limitations due to the system size Linke, Methods Enzymol. 2009, Cuypers et al., Chemosphere 2002,
28 COSMOmic COSMO-RS Conductor like Screening Model for Real Solvents based on quantum chemistry and statistical thermodynamics COSMOmic extension of COSMO-RS for anisotropic systems (membranes, micelles) Aggregates are radially divided in layers Probability of a solute to be suited in each layer can be calculated Chemical potential: Z X X r d r, d r d X M, M, res M, comb, Partition function: X M n i Z Probability: X M ( r i ) Z X m r i r X M i X Z M n i m i X M r, d exp kt d r Free energy profile r layer; d direction of solute Partition coefficient Klamt et al., J. Phys. Chem. B 2008,
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