Predicting Octanol/Water Partition Coefficients of Alcohol Ethoxylate Surfactants Using a Combination of Molecular Dynamics and the Conductor-like Screening Model for Realistic Solvents

Yamin, Peyman; Isele-Holder, Rolf E.; Leonhard, Kai

doi:10.1021/acs.iecr.5b04955

Cited by 12 publications

(13 citation statements)

References 45 publications

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“…It has been advised [48] that log K ow data for organics derived from software packages should be used cautiously as they cannot always cope with the complex and/or ionisable compounds. A more recent study [49] used a combination of molecular dynamics simulations and the quantum chemical conductor-like screening model for realistic solvents (COSMO-RS). A weight of evidence (WoE) approach is a reasonable approach to take for non-ionic surfactants using experimental and predicted values, given the greater degree of correlation and lower incidence of prediction errors between slow-stirring log K ow /D values and log K ow /D predictions using various methods.…”

Section: Discussionmentioning

confidence: 99%

A comparison of log Kow (n-octanol–water partition coefficient) values for non-ionic, anionic, cationic and amphoteric surfactants determined using predictions and experimental methods

et al. 2019

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Background: Surfactants are widely used across the globe both in industrial and consumer products. The n-octanol/ water partition ratio or coefficient (log K ow) and n-octanol/water distribution coefficient (log D) are key parameters in environmental risk assessment of chemicals as they are often used to estimate the environmental fate and bioavailability and thus exposure and toxicity of a compound. Determining log K ow data for surfactants is a technical challenge due to their amphiphilic properties. Currently several existing experimental OECD methods (e.g. slow-stirring, HPLC, solubility ratio) and QSPR models are available for log K ow /D measurement or prediction. However, there are concerns that these methods have not been fully validated for surfactants and may not be applicable due to the specific phase behaviour of surfactants. Results: The current methods were evaluated for the four surfactant classes (non-ionic, anionic, cationic and amphoteric). The solubility ratio approach, based on comparative n-octanol and water solubility measurements, did not generate robust or accurate data. The HPLC method generates consistently higher log K ow values than the slowstirring method for non-ionics, but this positive bias could be removed using reference surfactants with log K ow values determined using the slow-stirring method. The slow-stirring method is the most widely applicable experimental method for generating log K ow /D data for all the surface-active test compounds. Generally, QSPR-predicted log K ow /D values do not correlate well with experimental values, apart for the group of non-ionic surfactants. Relatively, large differences in predicted log K ow /D values were observed when comparing various QSPR models, which were most noticeable for the ionised surfactants. Conclusions: The slow-stirring method is the most widely applicable experimental method for generating log K ow /D data for all the four surfactant classes. A weight of evidence approach is considered appropriate for non-ionic surfactants using experimental and model predications. However, it is more difficult to apply this approach to ionisable surfactants. Recommendations are made for the preferred existing QSPR predictive methods for determination of log K ow /D values for the surfactant classes. Investigation of newer alternative experimental log K ow methods as well

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Section: Discussionmentioning

confidence: 99%

A comparison of log Kow (n-octanol–water partition coefficient) values for non-ionic, anionic, cationic and amphoteric surfactants determined using predictions and experimental methods

et al. 2019

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“…Frequency analyses were performed after geometry optimization to corroborate the minimum and to compare with experimental infrared spectra. Time-dependent density functional theory (TDDFT) was used at the same level of theory to calculate excitation energy with the conductor-like screening model for realistic solvents (COSMO) (Sinnecker et al, 2006 ; Mosquera and Wasserman, 2015 ; Simpson et al, 2015 ; Yamin et al, 2016 ). Three different media were considered for calculations (dichloromethane, acetonitrile, and DMSO) to estimate the hydrogen bond (IHB) stability and to visualize the possible conformational changes due to the solvent polarity.…”

Section: Experimental Computational Methods and Biological Essaysmentioning

confidence: 99%

Two New Fluorinated Phenol Derivatives Pyridine Schiff Bases: Synthesis, Spectral, Theoretical Characterization, Inclusion in Epichlorohydrin-β-Cyclodextrin Polymer, and Antifungal Effect

et al. 2018

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It has been reported that the structure of the Schiff bases is fundamental for their function in biomedical applications. Pyridine Schiff bases are characterized by the presence of a pyridine and a phenolic ring, connected by an azomethine group. In this case, the nitrogen present in the pyridine is responsible for antifungal effects, where the phenolic ring may be also participating in this bioactivity. In this study, we synthesized two new pyridine Schiff Bases: (E)-2-[(3-Amino-pyridin-4-ylimino)-methyl]-4,6-difluoro-phenol (F1) and (E)- 2-[(3-Amino-pyridin-4-ylimino)-methyl]-6-fluoro-phenol (F2), which only differ in the fluorine substitutions in the phenolic ring. We fully characterized both F1 and F2 by FTIR, UV-vis, 1H; 13C; 19F-NMR, DEPT, HHCOSY, TOCSY, and cyclic voltammetry, as well as by computational studies (DFT), and NBO analysis. In addition, we assessed the antifungal activity of both F1 (two fluorine substitution at positions 4 and 6 in the phenolic ring) and F2 (one fluorine substitution at position 6 in the phenolic ring) against yeasts. We found that only F1 exerted a clear antifungal activity, showing that, for these kind of Schiff bases, the phenolic ring substitutions can modulate biological properties. In addition, we included F1 and F2 into in epichlorohydrin-β-cyclodextrin polymer (βCD), where the Schiff bases remained inside the βCD as determined by the ki, TGA, DSC, and SBET. We found that the inclusion in βCD improved the solubility in aqueous media and the antifungal activity of both F1 and F2, revealing antimicrobial effects normally hidden by the presence of common solvents (e.g., DMSO) with some cellular inhibitory activity. The study of structural prerequisites for antimicrobial activity, and the inclusion in polymers to improve solubility, is important for the design of new drugs.

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“…These methods include quantitative structure-property relationships (QSPR) [6,7]; and atom-based [8], and quantum chemistry motivated methods such as COSMOtherm/COSMO-RS [9][10][11]. Computer simulations, e. g. molecular dynamics (MD) or Monte Carlo (MC) methods using atom-based potential functions or coarse-grained force-fields such as the MARTINI force field [12], provide an additional route to the prediction of log P for small or medium size solute molecules [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. There have also been attempts to use multiscale simulation methods mixing atomistic and coarse-grained potentials [13,30].…”

Section: Partition Coefficientsmentioning

confidence: 99%

Dissipative particle dynamics: Systematic parametrization using water-octanol partition coefficients

Anderson

Bray

Ferrante³

et al. 2017

The Journal of Chemical Physics

212

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We present a systematic, top-down, thermodynamic parametrization scheme for dissipative particle dynamics (DPD) using water-octanol partition coefficients, supplemented by water-octanol phase equilibria and pure liquid phase density data. We demonstrate the feasibility of computing the required partition coefficients in DPD using brute-force simulation, within an adaptive semi-automatic staged optimization scheme. We test the methodology by fitting to experimental partition coefficient data for twenty one small molecules in five classes comprising alcohols and poly-alcohols, amines, ethers and simple aromatics, and alkanes (i.e., hexane). Finally, we illustrate the transferability of a subset of the determined parameters by calculating the critical micelle concentrations and mean aggregation numbers of selected alkyl ethoxylate surfactants, in good agreement with reported experimental values.

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Predicting Octanol/Water Partition Coefficients of Alcohol Ethoxylate Surfactants Using a Combination of Molecular Dynamics and the Conductor-like Screening Model for Realistic Solvents

Cited by 12 publications

References 45 publications

A comparison of log Kow (n-octanol–water partition coefficient) values for non-ionic, anionic, cationic and amphoteric surfactants determined using predictions and experimental methods

A comparison of log Kow (n-octanol–water partition coefficient) values for non-ionic, anionic, cationic and amphoteric surfactants determined using predictions and experimental methods

Two New Fluorinated Phenol Derivatives Pyridine Schiff Bases: Synthesis, Spectral, Theoretical Characterization, Inclusion in Epichlorohydrin-β-Cyclodextrin Polymer, and Antifungal Effect

Dissipative particle dynamics: Systematic parametrization using water-octanol partition coefficients

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