Predicting Abraham model solvent coefficients

Bradley, Jean‐Claude; Abraham, Michael H.; Acree, William E.; Lang, Andrew S.

doi:10.1186/s13065-015-0085-4

Cited by 47 publications

(28 citation statements)

References 27 publications

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“…In general, we expect the performance of our model to be better for compounds similar to those in the training set, apart from obvious outliers. However, there was no statistically significant performance differential between the interior and the periphery of the chemical space as has been found previously for other properties we have modeled using similar techniques [ 17 ]. We used the free-to-use DMax Chemistry Assistant Software [ 18 ] to help discover regions of the chemical space where our random forest model performs poorly (and conversely, well).…”

Section: Resultssupporting

confidence: 74%

Prediction of 1-octanol solubilities using data from the Open Notebook Science Challenge

Buonaiuto

Lang

2015

Chemistry Central Journal

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Background1-Octanol solubility is important in a variety of applications involving pharmacology and environmental chemistry. Current models are linear in nature and often require foreknowledge of either melting point or aqueous solubility. Here we extend the range of applicability of 1-octanol solubility models by creating a random forest model that can predict 1-octanol solubilities directly from structure.ResultsWe created a random forest model using CDK descriptors that has an out-of-bag (OOB) R2 value of 0.66 and an OOB mean squared error of 0.34. The model has been deployed for general use as a Shiny application.ConclusionThe 1-octanol solubility model provides reasonably accurate predictions of the 1-octanol solubility of organic solutes directly from structure. The model was developed under Open Notebook Science conditions which makes it open, reproducible, and as useful as possible.Graphical abstract:Electronic supplementary materialThe online version of this article (doi:10.1186/s13065-015-0131-2) contains supplementary material, which is available to authorized users.

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Section: Resultssupporting

confidence: 74%

Prediction of 1-octanol solubilities using data from the Open Notebook Science Challenge

Buonaiuto

Lang

2015

Chemistry Central Journal

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“…Solvent coefficients can be obtained from solubility or chromatographic data, from databases, or can be estimated from group-contribution methods. 23,31,35,36 (ii) Various more theoretical a priori calculation methods can be used to predict Gibbs energies of solvation. They can be divided into two categories: (a) Solvation models considering the solute molecule surrounded by a discrete number of solvent molecules: in this approach, the solvation quantities can be deduced from molecular simulation techniques (molecular dynamics or Monte Carlo) or integral equation theory.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Solvation Quantities from Experimental Thermodynamic Data: Development of the Comprehensive CompSol Databank for Pure and Mixed Solutes

Moine

Privat

Sirjean

et al. 2017

Journal of Physical and Chemical Reference Data

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The Gibbs energy of solvation measures the affinity of a solute for its solvent and is thus a key property for the selection of an appropriate solvent for a chemical synthesis or a separation process. More fundamentally, Gibbs energies of solvation are choice data for developing and benchmarking molecular models predicting solvation effects. The Comprehensive Solvation-CompSol-database was developed with the ambition to propose very large sets of new experimental solvation chemical-potential, solvation entropy, and solvation enthalpy data of pure and mixed components, covering extended temperature ranges. For mixed compounds, the solvation quantities were generated in infinite-dilution conditions by combining experimental values of pure-component and binary-mixture thermodynamic properties. Three types of binary-mixture properties were considered: partition coefficients, activity coefficients at infinite dilution, and Henry's-law constants. A rigorous methodology was implemented with the aim to select data at appropriate conditions of temperature, pressure, and concentration for the estimation of solvation data. Finally, our comprehensive CompSol database contains 21 671 data associated with 1969 pure species and 70 062 data associated with 14 102 binary mixtures (including 760 solvation data related to the ionic-liquid class of solvents). On the basis of the very large amount of experimental data contained in the CompSol database, it is finally discussed how solvation energies are influenced by hydrogen-bonding association effects.

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“…NaPB-sodium phosphate buffer, pH 6.8. It should be mentioned that Willauer et al in the study [41] of partitioning of a set of 29 organic compounds in PEG-2000-K 3 PO 4 ATPS described partition behavior of compounds by the so-called linear free energy relationship (LFER) model by Abraham [42][43][44][45]. It was concluded [41] that partitioning of organic compounds in PEGsalt ATPS is governed by the solute size, basicity, and aromaticity or halogenicity.…”

Section: Tablementioning

confidence: 99%

Analysis of partitioning of organic compounds and proteins in aqueous polyethylene glycol-sodium sulfate aqueous two-phase systems in terms of solute–solvent interactions

Silva

Ferreira

Madeira

et al. 2015

Journal of Chromatography A

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Partition behavior of nine small organic compounds and six proteins was examined in poly(ethylene glycol)-8000-sodium sulfate aqueous two-phase systems containing 0.5M osmolyte (sorbitol, sucrose, trehalose, TMAO) and poly(ethylene glycol)-10000-sodium sulfate system, all in 0.01M sodium phosphate buffer, pH 6.8. The differences between the solvent properties of the coexisting phases (solvent dipolarity/polarizability, hydrogen bond donor acidity, and hydrogen bond acceptor basicity) were characterized with solvatochromic dyes using the solvatochromic comparison method. Differences between the electrostatic properties of the phases were determined by analysis of partitioning of sodium salts of dinitrophenylated (DNP-) amino acids with aliphatic alkyl side-chain. It was found out that the partition coefficient of all compounds examined (including proteins) may be described in terms of solute-solvent interactions. The results obtained in the study show that solute-solvent interactions of nonionic organic compounds and proteins in polyethylene glycol-sodium sulfate aqueous two-phase system differ from those in polyethylene glycol-dextran system.

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Predicting Abraham model solvent coefficients

Cited by 47 publications

References 27 publications

Prediction of 1-octanol solubilities using data from the Open Notebook Science Challenge

Prediction of 1-octanol solubilities using data from the Open Notebook Science Challenge

Estimation of Solvation Quantities from Experimental Thermodynamic Data: Development of the Comprehensive CompSol Databank for Pure and Mixed Solutes

Analysis of partitioning of organic compounds and proteins in aqueous polyethylene glycol-sodium sulfate aqueous two-phase systems in terms of solute–solvent interactions

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