COSMO-RS blind prediction of distribution coefficients and aqueous pKa values from the SAMPL8 challenge.

The SAMPL8 blind prediction challenge, which addresses the acid/base dissociation constants (pKa) and the distribution coefficients (logD), was addressed by the Conductor like Screening Model for Realistic Solvation (COSMO-RS). Using the COSMOtherm implementation of COSMO-RS together with a rigorous conformational sampling, yielded logD predictions with a root mean square deviation (RMSD) of 1.36 log units over all 11 compounds and seven bi-phasic systems of the data set, which was the most accurate of all contest submissions (logD).For the SAMPL8 pKa competition, participants were asked to report the standard state free energies of all microstates, which were then used to calculate the macroscopic pKa. We have used COSMO-RS based linear free energy fit models to calculate the requested energies. The assignment of the calculated and experimental pKa values was made on the basis of the popular transitions, i.e. the transition hat was predicted by the majority of the submissions. With this assignment and a model that covers both, pKa and base pKa, we achieved an RMSD of 3.44 log units (18 pKa values of 14 molecules), which is the second place of the six ranked submissions. By changing to an assignment that is based on the experimental transition curves, the RMSD reduces to 1.65. In addition to the ranked contribution, we submitted two more data sets, one for the standard pKa model and one or the standard base pKa model of COSMOtherm. Using the experiment based assignment with the predictions of the two sets we received a RMSD of 1.42 log units (25 pKa values of 20 molecules). The deviation mainly arises from a single outlier compound, the omission of which leads to an RMSD of 0.89 log units.

Experimental Determination of Air/Water Partition Coefficients for 21 Per- and Polyfluoroalkyl Substances Reveals Variable Performance of Property Prediction Models.

Per- and polyfluoroalkyl substances (PFAS) are a group of chemicals of high environmental concern. However, reliable data for the air/water partition coefficients (Kaw), which are required for fate, exposure, and risk analysis, are available for only a few PFAS. In this study, Kaw values at 25 °C were determined for 21 neutral PFAS by using the hexadecane/air/water thermodynamic cycle. Hexadecane/water partition coefficients (KHxd/w) were measured with batch partition, shared-headspace, and/or modified variable phase ratio headspace methods and were divided by hexadecane/air partition coefficients (KHxd/air) to obtain Kaw values over 7 orders of magnitude (10-4.9 to 102.3). Comparison to predicted Kaw values by four models showed that the quantum chemically based COSMOtherm model stood out for accuracy with a root-mean-squared error (RMSE) of 0.42 log units, as compared to HenryWin, OPERA, and the linear solvation energy relationship with predicted descriptors (RMSE, 1.28-2.23). The results indicate the advantage of a theoretical model over empirical models for a data-poor class like PFAS and the importance of experimentally filling data gaps in the chemical domain of environmental interest. Kaw values for 222 neutral (or neutral species of) PFAS were predicted using COSMOtherm as current best estimates for practical and regulatory use.

COSMO-RS predictions of logP in the SAMPL7 blind challenge.

We applied the COSMO-RS method to predict the partition coefficient logP between water and 1-octanol for 22 small drug like molecules within the framework of the SAMPL7 blind challenge. We carefully collected a set of thermodynamically meaningful microstates, including tautomeric forms of the neutral species, and calculated the logP using the current COSMOtherm implementation on the most accurate level. With this approach, COSMO-RS was ranked as the 6st most accurate method (Measured by the mean absolute error (MAE) of 0.57) over all 17 ranked submissions. We achieved a root mean square deviation (RMSD) of 0.78. The largest deviations from experimental values are exhibited by five SAMPL molecules (SM), which seem to be shifted in most SAMPL7 contributions. In context with previous SAMPL challenges, COSMO-RS demonstrates a wide range of applicability and one of the best in class reliability and accuracy among the physical methods.

COSMOtherm as an Effective Tool for Selection of Deep Eutectic Solvents Based Ready-To-Use Extracts from Grasevina Grape Pomace.

The aim of this work is to develop an industrially suitable process for the sustainable waste disposal in wine production. The proposed process involves the development of an environmentally friendly method for the isolation of biologically active compounds from Grasevina grape pomace according to the green extraction principles, in order to obtain a ready-to-use extract. In this process, deep eutectic solvents (DES) were used as extraction solvents. Aiming to save time in selecting the optimal DES that would provide the most efficient Grasevina pomace polyphenols extraction, the user-friendly software COSMOtherm was used and 45 DES were screened. Moreover, the prepared extracts were chemically and biologically characterized to confirm their safety for human application. Computational and experimental results proved the applicability of COSMOtherm in the selection of the optimal DES for the environmentally friendly preparation of the ready-to-use extract from Grasevina grape pomace with expected application in the cosmetic industry.

COSMO-RS based predictions for the SAMPL6 logP challenge.

Within the framework of the 6th physical property blind challenge (SAMPL6) the authors have participated in predicting the octanol-water partition coefficients (logP) for several small drug like molecules. Those logP values where experimentally known by the organizers but only revealed after the submissions of the predictions. Two different sets of predictions were submitted by the authors, both based on the COSMOtherm implementation of COSMO-RS theory. COSMOtherm predictions using the FINE parametrization level (hmz0n) obtained the highest accuracy among all submissions as measured by the root mean squared error. COSMOquick predictions using a fast algorithm to estimate σ-profiles and an a posterio machine learning correction on top of the COSMOtherm results (3vqbi) scored 3rd out of 91 submissions. Both results underline the high quality of COSMO-RS derived molecular free energies in solution.

Sustainable isolation of ginger (Zingiber officinale) herbal dust bioactive compounds with favorable toxicological profile employing natural deep eutectic solvents (NADES).

The usage of ginger (Zingiber officinale) has increased in recent years due to its positive effect on human health affiliated with its richness in gingerols and shogaols. This study optimized the Ultrasound-assisted extraction (UAE) for better phenolic compounds isolation from ginger herbal dust (GHD), a filter tea industry by-product. The extraction was performed using raw and defatted GHD-previously processed by Supercritical fluid extraction - CO2. An additional advantage was using COSMOtherm software for 71 natural deep eutectic solvents (NADES) screening, to select the optimal one for GHD 6-gingerol recovery. As an optimal NADES, Malic acid:Glucose (MA:Glc) in the 1:1 ratio was determined. The optimal MA: Glc-based extract with a 6-gingerol content of 1.90±0.05 mg/g, an antioxidant activity of 321.28±5.09 µmol TE/g, and a favorable toxicological profile was obtained in 2 min of UAE under the sonication amplitude of 20 %, approving the benefits and the sustainability of the present study.

Screening of 6000 Compounds for Uncoupling Activity: A Comparison Between a Mechanistic Biophysical Model and the Structural Alert Profiler Mitotox.

Protonophoric uncoupling of phosphorylation is an important factor when assessing chemicals for their toxicity, and has recently moved into focus in pharmaceutical research with respect to the treatment of diseases such as cancer, diabetes, or obesity. Reliably identifying uncoupling activity is thus a valuable goal. To that end, we screened more than 6000 anionic compounds for in vitro uncoupling activity, using a biophysical model based on ab initio COSMO-RS input parameters with the molecular structure as the only external input. We combined these results with a model for baseline toxicity (narcosis). Our model identified more than 1250 possible uncouplers in the screening dataset, and identified possible new uncoupler classes such as thiophosphoric acids. When tested against 423 known uncouplers and 612 known inactive compounds in the dataset, the model reached a sensitivity of 83% and a specificity of 96%. In a direct comparison, it showed a similar specificity than the structural alert profiler Mitotox (97%), but much higher sensitivity than Mitotox (47%). The biophysical model thus allows for a more accurate screening for uncoupling activity than existing structural alert profilers. We propose to use our model as a complementary tool to screen large datasets for protonophoric uncoupling activity in drug development and toxicity assessment.

Sustainable Development and Storage Stability of Orange By-Products Extract Using Natural Deep Eutectic Solvents.

The citrus industry produces large amounts of waste rich in bioactive compounds that have important effects on human health. Their extraction was performed using organic solvents, and a greener alternative to those solvents are natural deep eutectic solvents (NADES). The present study aimed to obtain and optimize extracts rich in polyphenols and flavonoids from orange peels using NADES and monitor polyphenol stability in the extracts for 30 days. The software COSMOtherm (conductor-like screening model) was used to screen fourteen NADES. The most promising solvents were lactic acid:glucose (LA:Glu) with an extraction yield of 1932 ± 7.83 mgGAE/100 gdw for TPC (total polyphenol content) and 82.7 ± 3.0 mg/100 gdw for TFC (total flavonoid content) and in the case of L-proline:malic acid (LP:MA) was 2164 ± 5.17 mgGAE/100 gdw for TPC and 97.0 ± 1.65 mg/100 gdw for TFC. The extraction process using LA:Glu and LP:MA was optimized, and the results showed that the selected variables (%NADES, solid:liquid ratio, and extraction time) had a significant influence on the extraction of TPC and TFC. Results showed that NADES improve the stability of TPC. These findings revealed that NADES are efficient for the extraction of bioactive compounds from orange by-products, and these extracts can represent an alternative for the food industry to enrich food products with natural ingredients.

Environmental modelling of hexamethoxymethylmelamine, its transformation products, and precursor compounds: An emerging family of contaminants from tire wear.

Hexamethoxymethylmelamine (HMMM) is a polymer crosslinking agent used commercially to manufacture tires. HMMM is a ubiquitous contaminant in urban surface waters due to its presence in tire-wear particles and its tendency to be transported into receiving waters during rain events through road runoff. It has recently been determined that this chemical readily transforms into numerous other compounds, several of which have also been detected in the aquatic environment. However, there is limited knowledge about the fate and distribution of HMMM and its likely transformation products and precursor compounds. COSMO-RS solvation theory was used to estimate the physico-chemical properties of HMMM and 24 related derivatives, including their aqueous solubility, various partitioning properties, vapour pressure, and melting point. Using these properties as inputs to the Equilibrium Criterion (EQC) fugacity-based multimedia model, three different emission scenarios were modeled. Overall, these compounds were predicted to readily partition into aqueous media, with distributions in water increasing with the loss of methoxymethyl groups. In addition, the persistence of the transformation products of HMMM was predicted to decline with the extent of these transformations. The EQC model predictions indicate that these compounds are subject to overland transport into surface waters. This study provides insights into the fate and behaviour of HMMM and its transformation compounds and contributes to the growing literature on the hazards of organic chemicals derived from tire wear.

Novel Synthesis of Choline-Based Amino Acid Ionic Liquids and Their Applications for Separating Asphalt from Carbonate Rocks.

In this study, a series of choline-based amino acid ionic liquids have been synthesized in an economic method and are used to assist solvents with extracting asphalt from carbonate rocks. All of the ionic liquids perform well in extracting asphalt, especially choline histidine, by which the single-step recovery of asphalt is up to 91%. Furthermore, oil product with higher quality (fewer solids entrained) is also obtained. Molecular dynamics simulation and thermodynamic equilibrium method are applied to investigate the role of amino acid ionic liquids via interaction energy calculation and surface free energy calculations. The simulation results suggest that the ionic liquid phase is beneficial for the transfer of oil fraction from the carbonate surface to the organic solvent phase. Moreover, the results of simulated calculation show that the introduction of a functional group with conjugated structures into ionic liquid, such as an imidazole ring and a benzene ring, is beneficial for enhancing oil recovery, which are in accordance with the results of experimental tests.

Polydimethylsiloxane-air partition ratios for semi-volatile organic compounds by GC-based measurement and COSMO-RS estimation: Rapid measurements and accurate modelling.

Polydimethylsiloxane (PDMS) shows promise for use as a passive air sampler (PAS) for semi-volatile organic compounds (SVOCs). To use PDMS as a PAS, knowledge of its chemical-specific partitioning behaviour and time to equilibrium is needed. Here we report on the effectiveness of two approaches for estimating the partitioning properties of polydimethylsiloxane (PDMS), values of PDMS-to-air partition ratios or coefficients (KPDMS-Air), and time to equilibrium of a range of SVOCs. Measured values of KPDMS-Air, Exp' at 25 °C obtained using the gas chromatography retention method (GC-RT) were compared with estimates from a poly-parameter free energy relationship (pp-FLER) and a COSMO-RS oligomer-based model. Target SVOCs included novel flame retardants (NFRs), polybrominated diphenyl ethers (PBDEs), polycyclic aromatic hydrocarbons (PAHs), organophosphate flame retardants (OPFRs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs). Significant positive relationships were found between log KPDMS-Air, Exp' and estimates made using the pp-FLER model (log KPDMS-Air, pp-LFER) and the COSMOtherm program (log KPDMS-Air, COSMOtherm). The discrepancy and bias between measured and predicted values were much higher for COSMO-RS than the pp-LFER model, indicating the anticipated better performance of the pp-LFER model than COSMO-RS. Calculations made using measured KPDMS-Air, Exp' values show that a PDMS PAS of 0.1 cm thickness will reach 25% of its equilibrium capacity in ∼1 day for alpha-hexachlorocyclohexane (α-HCH) to âˆ¼ 500 years for tris (4-tert-butylphenyl) phosphate (TTBPP), which brackets the volatility range of all compounds tested. The results presented show the utility of GC-RT method for rapid and precise measurements of KPDMS-Air.

Efficacy of bi-component cocrystals and simple binary eutectics screening using heat of mixing estimated under super cooled conditions.

The values of excess heat characterizing sets of 493 simple binary eutectic mixtures and 965 cocrystals were estimated under super cooled liquid condition. The application of a confusion matrix as a predictive analytical tool was applied for distinguishing between the two subsets. Among seven considered levels of computations the BP-TZVPD-FINE approach was found to be the most precise in terms of the lowest percentage of misclassified positive cases. Also much less computationally demanding AM1 and PM7 semiempirical quantum chemistry methods are likewise worth considering for estimation of the heat of mixing values. Despite intrinsic limitations of the approach of modeling miscibility in the solid state, based on components affinities in liquids under super cooled conditions, it is possible to define adequate criterions for classification of coformers pairs as simple binary eutectics or cocrystals. The predicted precision has been found as 12.8% what is quite accepted, bearing in mind simplicity of the approach. However, tuning theoretical screening to such precision implies the exclusion of many positive cases and this wastage exceeds 31% of cocrystals classified as false negatives.

Prediction of partition coefficients for complex environmental contaminants: Validation of COSMOtherm, ABSOLV, and SPARC.

Prediction of partition coefficients is essential for screening of environmentally relevant compounds. Prediction methods using only the molecular structure as input are especially useful for this purpose. In the present study, the authors validated 3 prediction method-COSMOtherm, ABSOLV, and SPARC-which are based on more mechanistic approaches than most other quantitative structure-activity relationships. Validation was based on a consistent experimental data set of up to 270 compounds, mostly pesticides and flame retardants. The validation systems included 3 gas chromatographic (GC) columns and 4 liquid/liquid systems that represent all relevant types of intermolecular interactions. Results revealed that the overall prediction accuracy of COSMOtherm and ABSOLV is comparable, whereas SPARC performance is substantially lower than the other methods. For instance, the root mean squared error for the 4 liquid/liquid partition coefficients was 0.65 log units to 0.93 log units for COSMOtherm, 0.64 log units to 0.95 log units for ABSOLV, and 1.43 to 2.85 log units for SPARC. In addition, version and parameterization influences of COSMOtherm on the prediction accuracy were determined.