Empirical regressions between system parameters and solute descriptors of polyparameter linear free energy relationships (PPLFERs) for predicting solvent-air partitioning
TL;DR: In this paper, empirical regressions are used to predict the equilibrium partitioning of solutes between two phases, referred to as a system, which is the case in which the relationship between solute and solvent properties is most clear.
About: This article is published in Fluid Phase Equilibria.The article was published on 2021-07-15. It has received 7 citations till now.
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TL;DR: In this paper , the authors developed quantitative structure property relations (QSPRs) between solutes and system parameters to predict equilibrium partitioning of solutes in neutral organic liquid solvent-air systems.
Abstract: Abstract Poly-parameter Linear Free Energy Relationships (PPLFERs) based on the Abraham solvation model are a useful tool for predicting and interpreting equilibrium partitioning of solutes in solvent systems. The focus of this work is neutral organic solutes partitioning in neutral organic liquid solvent-air systems. This is a follow-up to previous work (Brown, 2021) which developed predictive empirical correlations between solute descriptors and system parameters, allowing system parameters to be predicted from the solute descriptors of the solvent. A database of solute descriptors, and a database of system parameters supplemented by empirical predictions, form the basis for the development of new Quantitative Structure Property Relationships (QSPRs). A total of 11 QSPRs have been developed for the E , S , A , B and L solute descriptors, and the s , a , b , v , l , and c system parameters. The QSPRs were developed using a group-contribution method referred to as Iterative Fragment Selection. The method includes robust internal and external model validation and a well-defined Applicability Domain, including estimates of prediction uncertainty. System parameters can also be predicted by combining the solute descriptor QSPRs and the empirical correlations. The predictive power of PPLFERs applied using different combinations of experimental data, empirical correlations, and QSPRs are externally validated by predicting partition ratios between solvents and air. The uncertainty for predicting the log 10 K SA of diverse solutes in diverse solvents using only the new QSPRs and empirical correlations is estimated to be one log 10 unit or less.
13 citations
01 Jan 2017
TL;DR: In this paper, a gas chromatographic headspace analysis method was used to experimentally determine gas-to-liquid partition coefficients and infinite dilution activity coefficients for 29 liquid organic solutes dissolved in triethylene glycol at 298.15
Abstract: A gas chromatographic headspace analysis method was used to experimentally determine gas-to-liquid partition coefficients and infinite dilution activity coefficients for 29 liquid organic solutes dissolved in triethylene glycol at 298.15 K. Solubilities were also determined at 298.15 K for 23 crystalline nonelectrolyte organic compounds in triethylene glycol based on spectroscopic absorbance measurements. The experimental results of the headspace chromatographic and spectroscopic solubility measurements were converted to gas-to-triethylene glycol and water-to-triethylene glycol partition coefficients, and molar solubility ratios using standard thermodynamic relationships. Expressions were derived for solute transfer into triethylene glycol by combining our measured experimental values with published literature data. Mathematical correlations based on the Abraham model describe the observed partition coefficient and solubility data to within 0.16 log10 units (or less).
12 citations
TL;DR: The transfer of neutral compounds between immiscible phases in chromatographic or environmental systems can be described by six solute properties (solute descriptors) using the solvation parameter model as mentioned in this paper .
10 citations
TL;DR: In this article , the authors derived Abraham model expressions for solute transfer into the tert-butyl acetate mono-solvent and provided an accurate mathematical description of the observed experimental data.
Abstract: Experimental solubilities were determined for 31 solid nonelectrolyte organic compounds dissolved in tert-butyl acetate at 298.15 K. Results of the experimental measurements were combined with published mole fraction solubility data for two lipid-lowering medicinal compounds (lovastatin and simvastatin) in order to derive Abraham model expressions for solute transfer into the tert-butyl acetate mono-solvent. The derived correlations provided an accurate mathematical description of the observed experimental data. As part of the current study, previously published Abraham model solvent correlations for both ethyl acetate and butyl acetate were updated using much larger datasets that contained an additional 64 and 35 experimental data points, respectively. The mathematical correlations presented in the current study describe the observed solubility ratios of solutes dissolved in tert-butyl acetate, ethyl acetate, and butyl acetate to within an overall standard deviation of 0.15 log units or less.
6 citations
TL;DR: Abraham model correlations have been used to predict a number of very important chemical and thermodynamic properties including partition coefficients, molar solubility ratios, gas-liquid chromatographic and HPLC retention data, infinite dilution activity coefficients and molar enthalpies of solvation as discussed by the authors .
Abstract: Abraham model L solute descriptors have been determined for 149 additional C11 to C42 monomethylated and polymethylated alkanes based on published Kovat’s retention indices based upon gas–liquid chromatographic measurements. The calculated solute descriptors, in combination with previously published Abraham model correlations, can be used to predict a number of very important chemical and thermodynamic properties including partition coefficients, molar solubility ratios, gas–liquid chromatographic and HPLC retention data, infinite dilution activity coefficients, molar enthalpies of solvation, standard molar vaporization and sublimation at 298 K, vapor pressures, and limiting diffusion coefficients. The predictive computations are illustrated by estimating both the standard molar enthalpies of sublimation and the enthalpies of solvation in benzene for the monomethylated and polymethylated alkanes considered in the current study.
2 citations
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TL;DR: According to Henry's law, the equilibrium ratio between the abundances in the gas phase and in the aqueous phase is constant for a dilute solution as discussed by the authors, and a compilation of 17 350 values of Henry's Law constants for 4632 species, collected from 689 references is available at http://wwwhenrys-law.org
Abstract: Many atmospheric chemicals occur in the gas phase as well as in liquid cloud droplets and aerosol particles Therefore, it is necessary to understand the distribution between the phases According to Henry's law, the equilibrium ratio between the abundances in the gas phase and in the aqueous phase is constant for a dilute solution Henry's law constants of trace gases of potential importance in environmental chemistry have been collected and converted into a uniform format The compilation contains 17 350 values of Henry's law constants for 4632 species, collected from 689 references It is also available at http://wwwhenrys-laworg
1,935 citations
TL;DR: Evidence is presented that only models that have been validated externally, after their internal validation, can be considered reliable and applicable for both external prediction and regulatory purposes.
Abstract: The recent REACH Policy of the European Union has led to scientists and regulators to focus their attention on establishing general validation principles for QSAR models in the context of chemical regulation (previously known as the Setubal, nowadays, the OECD principles). This paper gives a brief analysis of some principles: unambiguous algorithm, Applicability Domain (AD), and statistical validation. Some concerns related to QSAR algorithm reproducibility and an example of a fast check of the applicability domain for MLR models are presented. Common myths and misconceptions related to popular techniques for verifying internal predictivity, particularly for MLR models (for instance crossvalidation, bootstrap), are commented on and compared with commonly used statistical techniques for external validation. The differences in the two validating approaches are highlighted, and evidence is presented that only models that have been validated externally, after their internal validation, can be considered reliable and applicable for both external prediction and regulatory purposes. (“Validation is one of those words...that is constantly used and seldom defined” as stated by A. R. Feinstein in the book Multivariate Analysis: An Introduction, Yale University Press, New Haven, 1996).
1,697 citations
TL;DR: It is concluded that for processes that entail transfer of a solute from one phase to another, only a small number of solute descriptors is needed to provide a reasonably accurate analysis of the process.
832 citations
TL;DR: In this article, the authors used the relationship Lw=L16/P where Lw is the Ostwald solubility coefficient on hexadecane at 298 K.
Abstract: The solubility of 408 gaseous compounds in water at 298 K has been correlated through eqn. (i), where the solubility is expressed as the Ostwald solubility coefficient, Lw, and the solute explanatory variables are R2 an excess molar refraction, π2H the dipolarity/polarizability, Σα2H and Σβ2H the effective hydrogen-bond acidity and basicity, and Vx the McGowan characteristic volume. A similar equation using the log L16 parameter instead of Vx can also be used; L16 is the Ostwald solubility coefficient on hexadecane at 298 K. log Lw=–0.994 + 0.577R2+ 2.549 π2H+ 3.813Σα2H+ 4.841Σβ2H– 0.869 Vx(i), n= 408 ρ= 0.9976 sd = 0.151 F= 16810 The main factors leading to increased solubility are solute π2H, Σα2H and Σβ2H values; conversely, the corresponding properties of water are dipolarity/polarizability, hydrogen-bond basicity and hydrogen-bond acidity. Solute size plays a minor role, and slightly decreases solubility, contrary to observations on all non-aqueous solvents. It is shown that this peculiar behaviour of water is due to (a) a greater increase in the unfavourable cavity effect with increase in solute size, for solvent water, and (b) a smaller increase in the favourable general dispersion interaction with size, for solvent water.A new method for the determination of log Lw values is put forward, using the relationship Lw=L16/P where L16 is as above, and P is either the water–hexadecane partition coefficient or the water–alkane partition coefficient. For 14 solutes using the former P-value, agreement with values calculated through eqn. (i) is 0.08 log units on average and for 45 solutes using the latter P-value, the corresponding agreement is 0.15 log units, with log Lw values ranging up to 8 log units.
463 citations
TL;DR: This study aims to develop robust QSAR/QSPR models for chemical properties of environmental interest that can be used for regulatory purposes and uses data from the publicly available PHYSPROP database, a set of 13 common physicochemical and environmental fate properties.
Abstract: The collection of chemical structure information and associated experimental data for quantitative structure–activity/property relationship (QSAR/QSPR) modeling is facilitated by an increasing number of public databases containing large amounts of useful data. However, the performance of QSAR models highly depends on the quality of the data and modeling methodology used. This study aims to develop robust QSAR/QSPR models for chemical properties of environmental interest that can be used for regulatory purposes. This study primarily uses data from the publicly available PHYSPROP database consisting of a set of 13 common physicochemical and environmental fate properties. These datasets have undergone extensive curation using an automated workflow to select only high-quality data, and the chemical structures were standardized prior to calculation of the molecular descriptors. The modeling procedure was developed based on the five Organization for Economic Cooperation and Development (OECD) principles for QSAR models. A weighted k-nearest neighbor approach was adopted using a minimum number of required descriptors calculated using PaDEL, an open-source software. The genetic algorithms selected only the most pertinent and mechanistically interpretable descriptors (2–15, with an average of 11 descriptors). The sizes of the modeled datasets varied from 150 chemicals for biodegradability half-life to 14,050 chemicals for logP, with an average of 3222 chemicals across all endpoints. The optimal models were built on randomly selected training sets (75%) and validated using fivefold cross-validation (CV) and test sets (25%). The CV Q2 of the models varied from 0.72 to 0.95, with an average of 0.86 and an R2 test value from 0.71 to 0.96, with an average of 0.82. Modeling and performance details are described in QSAR model reporting format and were validated by the European Commission’s Joint Research Center to be OECD compliant. All models are freely available as an open-source, command-line application called OPEn structure–activity/property Relationship App (OPERA). OPERA models were applied to more than 750,000 chemicals to produce freely available predicted data on the U.S. Environmental Protection Agency’s CompTox Chemistry Dashboard.
271 citations