Polyparameter Linear Free Energy Relationships Research Articles

Prediction of sorption of aromatic and aliphatic organic compounds by carbon nanotubes using poly-parameter linear free-energy relationships

The accurate prediction of distribution coefficients of organic compounds from water to carbon-based nanomaterials (CNM) is of major importance for the understanding of environmental processes and a risk assessment of released CNM. Poly-parameter linear free-energy relationships (ppLFER) have previously been shown to offer such an accurate prediction of sorption processes. The aim of this study was to identify and quantify the contribution of individual molecular interactions to overall sorption by multi-walled carbon nanotubes (MWCNTs). To this end, a large data set of experimental sorption isotherms by MWCNTs of 20 aliphatic and 14 aromatic compounds covering various relevant molecular interactions was produced. A thermodynamic cycle was used to obtain MWCNT-air distribution coefficients (KMWCNT/a) for the interpretation of direct sorbate-MWCNTs interactions. The thereby derived ppLFER log KMWCNT/a = (0.59 ± 0.59)E + (2.23 ± 0.59)S + (3.90 ± 0.67)A + (3.23 ± 0.71)B + (0.98 ± 0.17)L − (0.05 ± 0.50) shows the contribution of non-specific interactions, represented by the hexadecane-air partitioning constant (L), and specific interactions related to the solute polarity (S) as well as the H-bond interactions (A, B). Measured MWCNT-water distribution coefficients were clearly more accurately calculated by the ppLFER equations (R2 0.85–0.86) compared to the classical prediction by single parameter model based on the octanol–water partitioning constant (R2 0.64–0.78). In addition, the ppLFER presented here allow a more accurately prediction of sorption by MWCNTs compared to literature ppLFER, especially for aliphatic compounds and at environmentally relevant concentrations.

Predicting Partition Coefficients of Polyfluorinated and Organosilicon Compounds using Polyparameter Linear Free Energy Relationships (PP-LFERs)

The environmental behavior, fate, and effects of polyfluorinated compounds (PFCs) and organosilicon compounds (OSCs) have received increasing attention in recent years. In this study, polyparameter linear free energy relationships (PP-LFERs) were evaluated for predicting partition coefficients of neutral PFCs and OSCs, using experimental data for fluorotelomer alcohols (FTOHs) and cyclic volatile methylsiloxanes (cVMS) reported in the literature and measured newly for this work. It was found that the recently proposed PP-LFER model that uses the McGowan characteristic volume (V), the logarithmic hexadecane-air partition coefficient (L), and three polar interaction descriptors can accurately describe partition coefficients of PFCs and OSCs. The prediction errors were <1 log unit when literature descriptors were used, and the errors were reduced to <0.2 log units on average by further optimization of the descriptors. Surprisingly, the conventional forms of PP-LFERs that include the excess molar refraction (E) sometimes led to substantial errors (>1 log unit) even with optimized parameters. The system parameters for octanol-water, air-water, octanol-air, oil-water, liposome-water, and organic carbon-water partition coefficients as well as the solute descriptors for FTOHs and cVMS were recalibrated in this work, which should provide even more reliable predictions of partition coefficients. The results also confirm the consistency of the published experimental partition coefficients for FTOHs and cVMS.

Concentration-dependent polyparameter linear free energy relationships to predict organic compound sorption on carbon nanotubes

Adsorption of organic compounds on carbon nanotubes (CNTs), governed by interactions between molecules and CNTs surfaces, is critical for their fate, transport, bioavailability and toxicity in the environment. Here, we report a promising concentration-dependent polyparameter linear free energy relationships (pp-LFERs) model to describe the compound-CNTs interactions and to predict sorption behavior of chemicals on CNTs in a wide range of concentrations (over five orders of magnitude). The developed pp-LFERs are able to capture the dependence of the ki on equilibrium concentration. The pp-LFERs indexes [r, p, a, b, v] representing different interactions are found to have a good relationship with the aqueous equilibrium concentrations of compounds. This modified model can successfully interpret the relative contribution of each interaction at a given concentration and reliably predict sorption of various chemicals on CNTs. This approach is expected to help develop a better environmental fate and risk assessment model.

Experimental Determination of Polyparameter Linear Free Energy Relationship (pp-LFER) Substance Descriptors for Pesticides and Other Contaminants: New Measurements and Recommendations

Well-calibrated polyparameter linear free energy relationships (pp-LFERs) are an accurate way to predict partition coefficients (K) for neutral organic chemicals. In this work, pp-LFER substance descriptors of 111 environmentally relevant substances, mainly pesticides, were determined experimentally using gas chromatographic (GC) retention times and liquid/liquid partition coefficients. The complete set of descriptors for 50 compounds are being reported here for the first time. Validation of the measured substance descriptors was done by comparing predicted and experimental log K for the systems octanol/water (Kow), water/air (Kwa), and organic carbon/water (Koc), all of which indicated a high reliability of pp-LFER predictions based on the determined descriptors (e.g., a root mean squared error of 0.39 for log Kow). The descriptors presented in this work in combination with existing pp-LFER system equations substantially extend (and in some cases correct) our knowledge on partition properties of these 111 chemicals. In addition, the results of this work provide insight on some general guidelines with respect to the method combination best suited for deriving descriptors for environmentally relevant compounds.

General Model for Estimating Partition Coefficients to Organisms and Their Tissues Using the Biological Compositions and Polyparameter Linear Free Energy Relationships

Equilibrium partition coefficients of organic chemicals from water to an organism or its tissues are typically estimated by using the total lipid content in combination with the octanol-water partition coefficient (K(ow)). This estimation method can cause systematic errors if (1) different lipid types have different sorptive capacities, (2) nonlipid components such as proteins have a significant contribution, and/or (3) K(ow) is not a suitable descriptor. As an alternative, this study proposes a more general model that uses detailed organism and tissue compositions (i.e., contents of storage lipid, membrane lipid, albumin, other proteins, and water) and polyparameter linear free energy relationships (PP-LFERs). The values calculated by the established PP-LFER-composition-based model agree well with experimental in vitro partition coefficients and in vivo steady-state concentration ratios from the literature with a root mean squared error of 0.32-0.53 log units, without any additional fitting. This model estimates a high contribution of the protein fraction to the overall tissue sorptive capacity in lean tissues (e.g., muscle), in particular for H-bond donor polar compounds. Direct model comparison revealed that the simple lipid-octanol model still calculates many tissue-water partition coefficients within 1 log unit of those calculated by the PP-LFER-composition-based model. Thus, the lipid-octanol model can be used as an order-of-magnitude approximation, for example, for multimedia fate modeling, but may not be suitable for more accurate predictions. Storage lipid-rich phases (e.g., adipose, milk) are prone to particularly large systematic errors. The new model provides useful implications for validity of lipid-normalization of concentrations in organisms, interpretation of biomonitoring results, and assessment of toxicity.

Determination of Polyparameter Linear Free Energy Relationship (pp-LFER) Substance Descriptors for Established and Alternative Flame Retardants

Polyparameter linear free energy relationships (pp-LFERs) can predict partition coefficients for a multitude of environmental and biological phases with high accuracy. In this work, the pp-LFER substance descriptors of 40 established and alternative flame retardants (e.g., polybrominated diphenyl ethers, hexabromocyclododecane, bromobenzenes, trialkyl phosphates) were determined experimentally. In total, 251 data for gas-chromatographic (GC) retention times and liquid/liquid partition coefficients (K) were measured and used to calibrate the pp-LFER substance descriptors. Substance descriptors were validated through a comparison between predicted and experimental log K for the systems octanol/water (K(ow)), water/air (K(wa)), organic carbon/water (K(oc)) and liposome/water (K(lipw)), revealing a high reliability of pp-LFER predictions based on our descriptors. For instance, the difference between predicted and experimental log K(ow) was <0.3 log units for 17 out of 21 compounds for which experimental values were available. Moreover, we found an indication that the H-bond acceptor value (B) depends on the solvent for some compounds. Thus, for predicting environmentally relevant partition coefficients it is important to determine B values using measurements in aqueous systems. The pp-LFER descriptors calibrated in this study can be used to predict partition coefficients for which experimental data are unavailable, and the predicted values can serve as references for further experimental measurements.

Partitioning of Neutral Organic Compounds to Structural Proteins

Protein-water partition coefficients (K(pw)) of neutral organic chemicals were measured using muscle proteins (from chicken, fish, and pig), collagen and gelatin. K(pw) values for these structural proteins were consistently lower than those of bovine serum albumin (BSA), indicating that the use of BSA as a model protein leads to an overestimation of K(pw) for structural proteins. Differences in K(pw) between chicken, fish, and pig muscle proteins were small. Across the structural proteins, K(pw) values were often in the order: muscle proteins > collagen ≥ gelatin. Differences in K(pw) between the structural proteins were relatively large (<2 log units) for nonpolar compounds, and much smaller or insignificant for polar compounds. There were correlations between log K(pw) of muscle proteins and log K(ow) (R(2) = 0.83-0.86, SD: 0.35-0.40, n = 45-46). The polyparameter linear free energy relationship (PP-LFER) models fit even better to the data (R(2) = 0.95, SD: 0.22). The good model fitting suggests that the reversible binding to muscle proteins can be considered to be nonspecific binding. There was an indication that some chemicals may sorb irreversibly to muscle proteins, which needs further research. We found that the partitioning to muscle protein is typically weaker than that to lipids, but that the protein partitioning of an H-bond donor compound can be as strong as the storage lipid partitioning.

Partitioning of Organic Chemicals to Storage Lipids: Elucidating the Dependence on Fatty Acid Composition and Temperature

Lipids serve as important compartments in partitioning of neutral organic chemicals into organisms. Storage lipids, made up of triglycerides with various fatty acids, are among the major classes of lipids. Here, we present experimental equilibrium partition data for diverse chemicals in fish oil, linseed oil, and goose fat at 37 °C. These data, in combination with data from the literature for olive oil and milk fat, show that the fatty acid composition of triglycerides has no significant influence on the partition coefficient. This result allows the derivation of a general predictive model for partitioning into storage lipids. We have collected storage lipid/water partition coefficients for 247 compounds to calibrate polyparameter linear free energy relationships (pp-LFERs) for 37 °C, which achieved a model fit with a root mean squared error of 0.20 log units. To extend the applicability of this model toward the aquatic food chain, we also measured fish oil partition data at 7 °C. The resulting enthalpies were used to calibrate an additional pp-LFER for the temperature dependence of storage lipid/water partitioning. This model allows us to estimate partition coefficients at desired temperatures that occur under typical ambient conditions.

Evaluating dissolved organic carbon–water partitioning using polyparameter linear free energy relationships: Implications for the fate of disinfection by-products

The partitioning of micropollutants to dissolved organic carbon (DOC) can influence their toxicity, degradation, and transport in aquatic systems. In this study carbon-normalized DOC–water partition coefficients (KDOC–w) were measured for a range of non-polar and polar compounds with Suwannee River fulvic acid (FA) using headspace and solid-phase microextraction (SPME) methods. The studied chemicals were selected to represent a range of properties including van der Waal forces, cavity formation and hydrogen bonding interactions. The KDOC–w values were used to calibrate a polyparameter linear free energy relationship (pp-LFER). The difference between experimental and pp-LFER calculated KDOC–w values was generally less than 0.3 log units, indicating that the calibrated pp-LFER could provide a good indication of micropollutant interaction with FA, though statistical analysis suggested that more data would improve the predictive capacity of the model. A pp-LFER was also calibrated for Aldrich humic acid (HA) using KDOC–w values collected from the literature. Both experimental and pp-LFER calculated KDOC–w values for Aldrich HA were around one order of magnitude greater than Suwannee River FA. This difference can be explained by the higher cavity formation energy in Suwannee River FA. Experimental and pp-LFER calculated KDOC–w values were compared for halogenated alkanes and alkenes, including trihalomethane disinfection by-products, with good agreement between the two approaches. Experimental and calculated values show that DOC–water partitioning is generally low; indicating that sorption to DOC is not an important fate process for these chemicals in the environment.

Estimating Phospholipid Membrane–Water Partition Coefficients Using Comprehensive Two-Dimensional Gas Chromatography

Recent studies have shown that membrane-water partition coefficients of organic chemicals can be used to predict bioaccumulation and type I narcosis toxicity more accurately than the traditional K(OW)-based approach. In this paper, we demonstrate how comprehensive two-dimensional gas chromatography (GC × GC) can be used to estimate such membrane-water partition coefficients (K(PLW)s), focusing in particular on phosphatidyl choline based lipids. This method performed well for a set of 38 compounds, including polycyclic aromatic hydrocarbons, polychlorinated benzenes and biphenyls, and substituted benzenes including some phenols and anilines. The average difference between the estimated and the measured log K(PLW) values of 0.47 log units is smaller than in the case of a log K(OW) correlation approach but larger than seen using a polyparameter linear free energy relationship based approach. However, the GC × GC based method presents the advantage that it can be applied to mixtures of chemicals that are not completely identified, such as petroleum hydrocarbon mixtures. At the same time, our application of the GC × GC method suffered larger errors when applied to certain hydrogen bonding compounds due to the inability of the GC × GC capillary columns phases that we used to interact with analytes via hydrogen bond donation/electron acceptance.

Abiotic Reduction Reactions of Dichloroacetamide Safeners: Transformations of “Inert” Agrochemical Constituents

Safeners are so-called "inert" constituents of herbicide formulations added to protect crops from the toxic effects of herbicides. We examined the reactivity of three dichloroacetamide safeners and 12 structural analogues [all neutral compounds of the form Cl(2)CXC(═O)NRR'; X = H, Cl; R-groups include alkyl, branched alkyl, n-allyl, and cyclic moieties] in one homogeneous and two heterogeneous reductant systems: solutions of Cr(H(2)O)(6)(2+), suspensions of Fe(II)-amended goethite, and suspensions of Fe(II)-amended hematite. Analyses of reaction products indicate each safener can undergo stepwise hydrogenolysis (replacement of chlorine by hydrogen) in each system at near-neutral pH. The first hydrogenolysis step generates compounds similar (in one case, identical) to herbicide active ingredients. Rates of product formation and (when reactions were sufficiently fast) parent loss were quantified; reaction rates in heterogeneous systems spanned 2 orders of magnitude and were strongly influenced by R-group structure. The length of n-alkyl R-groups exerted opposite effects on hydrogenolysis rates in homogeneous versus heterogeneous systems: as R-group size increased, reduction rates in heterogeneous systems increased, whereas reduction rates in the homogeneous system decreased. Branched alkyl R-groups decreased hydrogenolysis rates relative to their straight-chain homologues in both homogeneous and heterogeneous systems. Reaction rates in heterogeneous systems can be described via polyparameter linear free energy relationships employing molecular parameters likely to influence dichloroacetamide adsorption. The propensity of dichloroacetamide safeners to undergo reductive transformations into herbicide-like products challenges their classification as "inert" agrochemical ingredients.

Prediction and Experimental Evaluation of Soil Sorption by Natural Hormones and Hormone Mimics

Surface runoff from manure-fertilized fields is a significant source of endocrine-disrupting compounds (EDCs) in the environment. Sorption by soils may play a major role in the environmental fate of manure-borne EDCs, including 17α- and 17β-estradiol (17α-E2 and 17β-E2), estrone (E1), melengestrol acetate (MGA), 17α- and 17β-trenbolone (17α-TB and 17β-TB), trendione (TND), and zeranol (α-ZAL). As a measure of sorption behavior, the organic carbon-normalized partition coefficients (K(OC)) of 17β-E2, E1, MGA, and α-ZAL were experimentally determined for three agricultural soils with initial EDC concentrations spanning from ∼0.01 to >1 μM. Sorption isotherms were linear for most solute-soil combinations. Measured K(OC) values were compared to those predicted using a suite of single-parameter and polyparameter linear free energy relationships (sp- and pp-LFERs). Sp-LFER models were based on experimentally determined octanol-water partition coefficients (K(OW)), whereas pp-LFER solute descriptors were calculated indirectly from experimentally determined solvent-water partition coefficients or the program ABSOLV. Log K(OC) predictions by sp-LFERs were closest to the experimentally determined values, whereas pp-LFER predictions varied considerably due to uncertainties in both solute and sorbent descriptors determined by ABSOLV or estimates using the partition coefficient approach.

Salting-Out Effect in Aqueous NaCl Solutions: Trends with Size and Polarity of Solute Molecules

Salting-out in aqueous NaCl solutions is relevant for the environmental behavior of organic contaminants. In this study, Setschenow (or salting-out) coefficients (K(s) [M(-1)]) for 43 diverse neutral compounds in NaCl solutions were measured using a shared headspace passive dosing method and a negligible depletion solid phase microextraction technique. The results were used to calibrate and evaluate estimation models for K(s). The molar volume of the solute correlated only moderately with K(s) (R(2) = 0.49, SD = 0.052). The polyparameter linear free energy relationship (pp-LFER) model that uses five compound descriptors resulted in a more accurate fit to our data (R(2) = 0.83, SD = 0.031). The pp-LFER analysis revealed that Na(+) and Cl(-) in aqueous solutions increase the cavity formation energy cost and the polar interaction energies toward neutral organic solutes. Accordingly, the salting-out effect increases with the size and decreases with the polarity of the solute molecule. COSMO-RS, a quantum mechanics-based fully predictive model, generally overpredicted the experimental K(s), but the predicted values were moderately correlated with the experimental values (R(2) = 0.66, SD = 0.042). Literature data (n = 93) were predicted by the calibrated pp-LFER and COSMO-RS models with root mean squared errors of 0.047 and 0.050, respectively. This study offers prediction models to estimate K(s), allowing implementation of the salting-out effect in contaminant fate models, linkage of various partition coefficients (such as air-water, sediment-water, and extraction phase-water partition coefficients) measured for fresh water and seawater, and estimation of enhancement of extraction efficiency in analytical procedures.

Measurements and predictions of hexadecane/air partition coefficients for 387 environmentally relevant compounds

The logarithm of the hexadecane/air partition coefficient L is a common descriptor for non-specific interaction properties of solutes and is used in poly-parameter linear free energy relationships (pp-LFERs) to predict other partition coefficients. However, the L value data set available for complex and multifunctional substances is rather small. This limits the applicability of the pp-LFER equation. Hence, we experimentally determined L values for 387 complex compounds using GC-retention time measurements on a non-polar column (SPB™ Octyl). The target substances include environmentally relevant compounds such as pesticides, flame retardants and hormones. We determined L values that span a large range of 4.28-15.92. In addition to these experimental measurements several prediction tools (connectivity indices, SPARC, ABSOLV, COSMOthermX) for the L value were evaluated. The root mean squared errors (rmse) were 1.55 (connectivity indices), 1.28 (SPARC), 0.99 (ABSOLV) and 0.94 (COSMOthermX). The number of outliers (prediction error>3) was 18 (connectivity indices), 12 (SPARC), 2 (ABSOLV) and 0 (COSMOthermX). Based on these results the best prediction accuracy in this evaluation is reached by ABSOLV and COSMOthermX, whose results are comparable.

Serum Albumin Binding of Structurally Diverse Neutral Organic Compounds: Data and Models

Binding to serum albumin has a strong influence on freely dissolved, unbound concentrations of chemicals in vivo and in vitro. For neutral organic solutes, previous studies have suggested a log-log correlation between the albumin-water partition coefficient and the octanol-water partition coefficient (K(ow)) and postulated highly nonspecific binding that is mechanistically analogous to dissolution into solvents. These relationships and concepts were further explored in this study. Bovine serum albumin (BSA)-water partition coefficients (K(BSA/w)) were measured for 83 structurally diverse neutral organic chemicals in consistent experimental conditions. The correlation between log K(BSA/w) and log K(ow) was moderate, with R(2) = 0.76 and SD = 0.43. The log K(BSA/w) of low-polarity compounds including a series of chlorobenzenes and polycyclic aromatic hydrocarbons increased with log K(ow) linearly up to log K(ow) = 4-5, but then the linear relationship apparently broke off, and the increase became gradual. The fitting of polyparameter linear free energy relationship models with five solute descriptors was just comparable to that of the log K(ow) model (R(2) = 0.78-0.79, SD = 0.41-0.42); the relatively high SD obtained suggests that solvent dissolution models are not capable of modeling albumin binding accurately. A size limitation of the binding site(s) of albumin is suggested as a possible reason for the high SD. An equilibrium distribution model indicates that serum albumin generally has high contributions to the binding in the serum of polar compounds and relatively small low-polarity compounds, whereas albumin binding for large low-polarity compounds is outcompeted by the strong partitioning into lipids due to low relative affinity of albumin for these compounds.

Equilibrium Partition Coefficients of Diverse Polar and Nonpolar Organic Compounds to Polyoxymethylene (POM) Passive Sampling Devices

Equilibrium passive samplers (EPS) based on polyoxymethylene (POM) are increasingly used for determining freely dissolved water and pore water concentrations of hydrophobic organic compounds in the environment. Unlike other polymeric materials commonly used as EPS, namely poly(dimethylsiloxane) (PDMS) and low-density polyethylene (PE), POM is a polar polymer, containing repeating H-bond accepting ether units. Thus, POM is expected to be a more sensitive EPS than PDMS and PE for polar, H-bond donating compounds, such as many hormones, pharmaceuticals, and biocides. To better characterize the sorption capacity of POM for diverse polar and apolar compounds, equilibrium POM-water partition coefficients, K(POM/w), were measured for 56 compounds, including several classes of polar compounds and organochlorine pesticides. Using this data set and literature data, various POM-partitioning models were calibrated and validated for their ability to predict K(POM/w). The best performing models tested were an Abraham descriptor based polyparameter linear free energy relationship (PP-LFER) (SD = 0.24 log units) and COSMOthermX (SD = 0.37 log units). The performance of SPARC (SD = 0.61 log units) and log-log correlations with K(ow) (SD = 0.49 log units) were lower. A comparison with PDMS and PE confirmed expectations that POM exhibits a higher sensitivity for H-bond donating polar compounds than PDMS and PE do for these compounds. These findings expand the domain of chemicals for which POM can be used as an EPS sampler, and demonstrate that POM is as suitable a passive sampler for many polar organic compounds as it is for hydrophobic organic compounds.

Improving Predictability of Sediment-Porewater Partitioning Models using Trends Observed with PCB-Contaminated Field Sediments

More than 1900 sediment-water partitioning coefficients were measured for 58 polychlorinated biphenyl (PCB) congeners in 53 historically contaminated sediments collected from 10 urban and rural waterways in the United States and Canada. Freely dissolved porewater concentrations were determined using passive sampling with polyoxymethylene. Measured total organic carbon (TOC)/water partitioning coefficients, K(TOC), ranged from one to nearly three orders-of-magnitude higher than typical literature values based on spiking experiments and model predictions. Although total PCB concentrations ranged from 0.08 to 194 mg/kg, the more highly contaminated sediments showed only slightly lower K(TOC) values than less-contaminated sediments. No correlation was observed between log K(TOC) values and sediment TOC, black carbon (BC), or BC/TOC fractions (r(2) typically <0.1). Utilizing a two-carbon model incorporating anthropogenic BC did not improve predictions over a one-carbon TOC model. A comparison of models recently validated for field data showed that a coal-tar poly parameter linear-free energy relationship (PP-LFER) and a Raoult's Law model were successful at predicting average log K(TOC) values, without the need for any calibration or fitting (within a factor of 10 more than 90% of the time, and within a factor of 30 more than 99% of the time). Predictions were further improved by the introduction of a Weathering Factor (WF) that accounts for the relative depletion of lower molecular weight congeners due to weathering. Highly weathered sediments (with a WF near 1) tended to follow the coal-tar PP-LFER and Raoult's Law model the closest. Less-weathered sediments (with WF ≪ 1) sorbed less than predicted by these models. Noncalibrated WF inclusive coal-tar PP-LFER and Raoult's Law models performed as well or better than a quantitative-structure activity relationship (QSAR) model calibrated specifically to the data. These recommended partitioning models here can readily be used for all 209-PCB congeners.

Capacities of Membrane Lipids to Accumulate Neutral Organic Chemicals

Lipids have been considered as the predominant components for bioaccumulation of organic chemicals. However, differences in accumulation properties between different types of lipid (e.g., storage and membrane lipids) have rarely been considered. Moreover, in view of toxic effects on organisms, chemical accumulation specifically in biological membranes is of particular importance. In this review article, partition coefficients of 240 neutral organic compounds between liposomes (phospholipid membrane vesicles) and water (K(lipw)), reported in the literature or measured additionally for this work, were evaluated. Values of log K(lipw) and log K(ow) (octanol-water partition coefficients) differ by 0.4 on average. Polyparameter linear free energy relationships (PP-LFERs) can describe the log K(lipw) data even better (standard deviations = 0.28-0.31) than the log K(ow) model. Recent experimental data for highly hydrophobic compounds fit well to the PP-LFERs and do not indicate the existence of a previously postulated "hydrophobicity cutoff". Predictive approaches based only on the molecular structure (KOWWIN, SPARC, COSMOthermX, COSMOmic) were also evaluated for K(lipw) prediction. The PP-LFERs revealed that partition coefficients into membrane lipids can be two log units higher than those into storage lipids for H-bond donor compounds, suggesting that distinguishing between the two lipids is necessary to account for the bioaccumulation of these compounds, and that tissues rich in membrane lipids (e.g., kidneys, liver) instead of fat tissue can be the primary phase for accumulation.

Partitioning of polar and non-polar neutral organic chemicals into human and cow milk

The aim of this work was to develop a predictive model for milk/water partition coefficients of neutral organic compounds. Batch experiments were performed for 119 diverse organic chemicals in human milk and raw and processed cow milk at 37 °C. No differences (< 0.3 log units) in the partition coefficients of these types of milk were observed. The polyparameter linear free energy relationship model fit the calibration data well (SD = 0.22 log units). An experimental validation data set including hormones and hormone active compounds was predicted satisfactorily by the model. An alternative modelling approach based on log K ow revealed a poorer performance. The model presented here provides a significant improvement in predicting enrichment of potentially hazardous chemicals in milk. In combination with physiologically based pharmacokinetic modelling this improvement in the estimation of milk/water partitioning coefficients may allow a better risk assessment for a wide range of neutral organic chemicals.

Ionic Liquids: Predictions of Physicochemical Properties with Experimental and/or DFT-Calculated LFER Parameters To Understand Molecular Interactions in Solution

In this article, we present evolutionary models to predict the octanol-water partition coefficients (log P), water solubilities, and critical micelle concentrations (CMCs) of ionic liquids (ILs), as well as the anionic activity coefficients and hydrophobicities in pure water and octanol-water. They are based on a polyparameter linear free energy relationship (LFER) using measured and/or DFT-calculated LFER parameters: hydrogen-bonding acidity (A), hydrogen-bonding basicity (B), polarizability/dipolarity (S), excess molar refraction (E), and McGowan volume (V) of IL ions. With both calculated or experimental LFER descriptors of IL ions, the physicochemical parameters were predicted with an errors of 0.182-0.217 for the octanol-water partition coefficient and 0.131-0.166 logarithmic units for the water solubility. Because experimentally determined solute parameters of anions are not currently available, the CMC, anionic activity coefficient, and hydrophobicity were predicted with quantum-chemical methods with R(2) values of at least 0.99, as well as errors below 0.168 logarithmic units. These new approaches will facilitate the assessment of the technical applicability and environmental fate of ionic compounds even before their synthesis.