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The octanol-air partition ratio (K OA ) is a fundamental property used for screening chemicals for concern, depending on their potential to bioaccumulate and harm living systems. With millions of chemicals used in commerce, unfortunately, less than 800 compounds currently have experimentally measured K OA values due to limitations in traditional measurement techniques. We aimed to develop a direct gas chromatography retention time (GC-RT) method using a custom-packed column, with octanol as the stationary phase, for rapidly measuring K OA . We installed the column into a GC-mass spectrometry system and isothermally measured retention times of 15 volatile organic compounds. We calculated K OA values at experimental temperatures from the retention times and extrapolated the results to values at 25 °C using the Van't Hoff equation. Our directly measured log K OA values at 25 °C spanned 3.66 log units (0.820-4.48). Except for alcohols, our measured values agree with literature log K OA values (root mean square error, RMSE = 0.50). The discrepancy probably arose from differences in how well our method versus the literature methods capture measurement artifacts, specifically, gas-phase adsorption to the octanol phase and hydrogen bonding interactions. This proof-of-concept study demonstrates that our direct GC-RT method is promising for rapidly measuring K OA to support chemical risk assessment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Legacy brominated flame retardants, including polybrominated diphenyl ethers (PBDEs), have been classified as persistent organic pollutants and replaced with novel brominated flame retardants (NBFRs). The octanol-water partition coefficients (log K OW ) of NBFRs have been computationally estimated, but the log K OW values provided by these methods can differ by 1 to 3 orders of magnitude. Given the importance of this parameter in fate and toxicity models, we indirectly measured the log K OW values of eight NBFRs by their capacity factor (k') on a reversed-phase high-performance liquid chromatography (HPLC) C18 column by isocratic elution and compared these measured values with those estimated by nine computational models. Log K OW values were obtained for the NBFRs 1,2-bis(2,4,6-tribromophenoxy) ethane, pentabromobenzene, pentabromoethylbenzene, pentabromotoluene, 2-ethylhexyl 2,3,4,5-tetrabromobenzoate, allyl 2,4,6-tribromophenylether, 2,3-dibromopropyl-2,4,6-tribromophenyl ether, and bis(2-ethylhexyl) tetrabromophthalate. A training set of phthalates, polychlorinated biphenyls, PBDEs, and halogenated benzenes were chosen to obtain the log k'-log K OW calibration for the NBFRs. The computational models KowWIN, XLogP3, EAS-E Suite, COSMOtherm, DirectML, and Abraham polyparameter linear free energy relationships all predicted the log K OW values of the calibration compounds to within 1 order of magnitude without significant bias. The median of these models predicted log K OW values for the calibration compounds that were close to those known in the literature with root mean square error (RMSE) = 0.224 and for the NBFRs that were close to those measured by HPLC (RMSE = 0.334). Environ Toxicol Chem 2024;43:2105-2114. © 2024 SETAC., (© 2024 SETAC.)

Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome. RIFM staff are employees of the Research Institute for Fragrance Materials, Inc. (RIFM). The Expert Panel receives a small honorarium for time spent reviewing the subject work.

Five in vitro physicochemical systems have been evaluated in terms of its ability to emulate the skin permeation of neutral compounds: the permeation in two different PAMPA membranes, the classical octanol-water partition coefficient, and two biomimetic chromatography systems, one based in cerasome electrokinetic chromatography and another based in reversed-phase liquid chromatography measurements. The coefficients of the solvation parameter model equation of the mentioned systems have been compared to the ones of the skin permeation process through different comparison parameters. Moreover, a method to predict whether a physicochemical system is able to emulate satisfactorily a biological one, just by the analysis of the equation coefficients has been developed. Results reveal that the two PAMPA systems are a good choice to emulate directly the skin permeation of neutral compounds. Instead, the other three systems need a volume correction term to provide a satisfactory emulation. However, after the correction, all the evaluated systems show a similar ability to emulate well skin permeation, as predicted., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The solvation parameter model uses five system independent descriptors to characterize compound properties defined as excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity, A, hydrogen-bond basicity, B, and McGowan's characteristic volume, V, to model transfer properties between condensed phases. The V descriptor is assigned from structure. For compounds liquid at 20 °C the E descriptor can be assigned from the characteristic volume and its refractive index. The E descriptor for compounds solid at 20 °C and the S, A, and B descriptors are experimental properties traditionally assigned from chromatographic, liquid-liquid partition, and solubility measurements. In this report liquid-liquid partition constants in totally organic and aqueous biphasic systems are evaluated as a standalone technique for descriptor assignments. Using six totally organic biphasic systems the S, A, and B descriptors were assigned with an average absolute deviation (AAD) of about 0.04, 0.03, and 0.04, respectively, compared with the best estimate of the true descriptor values for 65 compounds. The E descriptor for compounds solid at 20 °C can only be estimated with an AAD of approximately 0.1. For six aqueous biphasic systems the B descriptor is assigned with a lower AAD of 0.028 and higher AAD of 0.08 and 0.05 for the S and A descriptors, respectively, than for the totally organic biphasic systems for compounds with a reliable value for the E descriptor. The preferred system for descriptor assignments utilizes both totally organic biphasic systems (heptane-1,1,1-trifluoroethanol, isopentyl ether-propylene carbonate, isopentyl ether-ethanolamine, heptane-ethylene glycol, heptane-formamide, and 1,2-dichloroethane-ethylene glycol) and aqueous biphasic systems (octanol-water, cyclohexane-water) with the possible substitution of some systems with alternative systems of similar selectivity. For 55 varied compounds this combination of eight organic and aqueous biphasic systems resulted in an AAD of approximately 0.03, 0.02, and 0.02 for the S, A, and B descriptors compared to the best estimate of the true descriptor value. For 30 compounds solid at 20 °C the AAD for the E descriptor of 0.11 is poorly assigned. The relative average absolute deviation in percent (RAAD) corresponds to 9.7 %, 3.1 %. 4.0 % and 8.3 % for E, S, A, and B, respectively, for the eight biphasic systems. Liquid-liquid partition is compared to reversed-phase liquid and gas chromatography as a standalone technique for descriptor assignments., Competing Interests: Declaration of competing interest The author declares that he has no conflicts of interest in connection with this study., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The host-seeking behavior of mosquitoes have long been established to be primarily odor-mediated. In this process, olfactory receptors (Ors) play a critical role. 1-Octen-3-ol is a common volatile compound that is attractive to hematophagous arthropods such as mosquitos. The olfactory receptor 8 (AaOr8) on the tip of the stylet and maxillary palp of Aedes aegypti is tuned to 1-octen-3-ol, which is required for mosquitoes to quickly find blood vessels from a vertebrate host. However, little is known about the interaction of AaOr8 with 1-octen-3-ol which was studied in vivo and in silico in this study. The molecular binding poses and energies between ligands and the receptor were investigated. Three mutants of AaOr8 were cloned and compared with in vivo calcium imaging utilizing heterologous expression systems. As a result, our findings imply that a genetic disruption including targeted modification of Ors genes may be used to reduce mosquito bites., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The rising demand from consumer goods and pharmaceutical industry is driving a fast expansion of newly developed chemicals. The conventional toxicity testing of unknown chemicals is expensive, time-consuming, and raises ethical concerns. The quantitative structure-property relationship (QSPR) is an efficient computational method because it saves time, resources, and animal experimentation. Advances in machine learning have improved chemical analysis in QSPR studies, but the real-world application of machine learning-based QSPR studies was limited by the unexplainable 'black box' feature of the machine learnings. In this study, multi-encoder structure-to-toxicity (S2T)-transformer based QSPR model was developed to estimate the properties of polychlorinated biphenyls (PCBs) and endocrine disrupting chemicals (EDCs). Simplified molecular input line entry systems (SMILES) and molecular descriptors calculated by the Dragon 6 software, were simultaneously considered as input of QSPR model. Furthermore, an attention-based framework is proposed to describe the relationship between the molecular structure and toxicity of hazardous chemicals. The S2T-transformer model achieved the highest R 2 scores of 0.918, 0.856, and 0.907 for logarithm of octanol-water partition coefficient (Log K OW ), octanol-air partition coefficient (Log K OA ), and bioconcentration factor (Log BCF) estimation of PCBs, respectively. Moreover, the attention weights were able to properly interpret the lateral (meta, para) chlorination associated with PCBs toxicity and environmental impact., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The octanol/water partition coefficient, P (logP), is a hydrophobicity index and is one of the determining factors of the pharmacokinetics of chemical compounds. LogP values obtained from in silico software, open chemistry databases, and in vitro liquid chromatography retention factors may vary. Some chemicals (boscalid, etoxazole, and permethrin) have up to four-order-magnitude differences in in silico/in vitro P values. This study aimed to evaluate the effects of logP values of these three compounds, along with bisphenol A, 1,2-dibromobenzene, tetrabromobisphenol A, trazodone, and triazolam, on the input parameters and output plasma/hepatic concentration-time profiles of simple physiologically based pharmacokinetic (PBPK) models. Although the blood-to-plasma concentration ratios (~0.9-0.6) were slightly affected by variations in logP values, logarithmic plasma unbound fraction values and liver-to-plasma partition coefficients (K p,h ) were, respectively, inversely and linearly correlated with logP values (K p,h was stable at ~6.7 for logP > 4). LogP was among the input parameters for previously established machine learning systems; consequently, the resulting logarithmic intrinsic clearance values were correlated with logP values in the range 2-8. However, the bioavailability, absorption rate constants, and volumes of distribution were not affected. PBPK-modeled plasma and hepatic maximum concentrations and areas under the concentration-time curves after virtual oral doses were mostly within ~0.5- to ~2-fold ranges, except for substances with low in vitro logP values, e.g., etoxazole and permethrin. These results suggest that in silico logP values are generally suitable for pharmacokinetic modeling; nevertheless, caution is needed for compounds with low in vitro logP values of ~2.

The octanol/water partition coefficient P (logP) is a hydrophobicity index and is one of the determining factors for the pharmacokinetics of orally administered substances because it influences membrane permeability. To illustrate the wide-ranging variety of compounds in the chemical space, a two-dimensional data plot consisting of 25 blocks was previously proposed based on a substance's in silico chemical descriptors. The logP values of approximately 200 diverse chemicals (test plus reference compounds covering all 25 blocks of the chemical space) were estimated experimentally using retention times in reverse-phase liquid chromatography; these values were compared with those of authentic reference compounds with established logP values (available for 17 of 60 reference substances in the Organization for Economic Co-operation and Development Test Guideline 117). The logP values of 140 of 165 chemicals successfully estimated using four different mobile phase conditions (pH 2, 4, 7, and 10 for molecular forms) correlated significantly with those calculated using the in silico packages ChemDraw and ACD/Percepta (r > 0.72). Although substances that neighbored authentic compounds in the chemical space had precisely correlated logP values estimated experimentally and in silico, some compounds that were more distant from authentic substances showed lower logP values than those estimated in silico. These results indicate that additional authentic reference materials with wider ranging chemical diversity and their logP values from reverse-phase liquid chromatography should be included in the international test guidance to promote simple and reliable estimation of octanol/water partition coefficients, which are important determinant factors for the pharmacokinetics of general chemicals.

The variety of polymers utilized in medical devices demands for testing of extractables and leachables according to ISO 10993-18:2020 in combination with ISO 10993-1:2018. The extraction of the materials involves the use of organic solvents as well as aqueous buffers to cover a wide range of polarity and pH-values, respectively. To estimate patient exposure to chemicals leaching from a polymer in direct body contact, simulating solvents are applied to best mimic the solubilization and partitioning behavior of the related tissue or body fluid. Here we apply linear solvation energy relationship (LSER) models to predict blood/water and adipose tissue/water partition coefficients. We suggest this predictive approach to project levels of potential leachables, design extraction experiments, and to identify the optimal composition of simulating extraction solvents. We compare our predictions to LSER predictions for commonly applied surrogates like ethanol/water mixtures, butanol, and octanol as well as olive oil, butanone, 1,4-dioxane for blood and adipose tissue, respectively. We therefore selected a set of 26 experimentally determined blood/water partition coefficients and 33 adipose tissue/water partition coefficients, where we demonstrate that based on the root mean squared error rmse the LSER approach performs better than surrogates like octanol or butanol and equally well as 60:40 ethanol/water for blood. For adipose tissue/water partitioning, the experimentally determined octanol/water partition coefficient performs best but the rmse is at the same range as our LSER approach based on experimentally determined descriptors. Further, we applied our approach for 248 extractables where we calculated blood/low density polyethylene (LDPE) and adipose tissue/LDPE partition coefficients. By this approach, we successfully identified chemicals of potential interest to a toxicological evaluation based on the total risk score., (© 2023 The Authors. Journal of Biomedical Materials Research Part B: Applied Biomaterials published by Wiley Periodicals LLC.)

The environmental partition properties of perfluoroalkyl and polyfluoroalkyl substances (PFAS) must be understood for their transport and fate analysis. In this study, isothermal gas chromatographic (GC) retention times of 60 neutral PFAS were measured using four columns with different stationary phase polarities, which indicated varying polar interactions exerted by these substances. The GC data were combined with new octanol/water partition coefficient data from this study and existing partition coefficient data from the literature and used to determine the polyparameter linear free energy relationship (PP-LFER) solute descriptors. A complete set of the solute descriptors was obtained for 47 PFAS, demonstrating the characteristic intermolecular interaction properties, such as hydrogen bonding capabilities influenced by the electron-withdrawing perfluoroalkyl group. The partition coefficients between octanol and water, air and water, and octanol and air predicted by the PP-LFER models agreed with those predicted by the quantum chemically based model COSMO therm , suggesting that both models are highly accurate for neutral PFAS and can fill the current large data gaps in partition property data. A chemical partitioning space plot was generated by using the PP-LFER-predicted partition coefficients, showing the primary importance of the air phase for the environmental distribution of nonpolar and weakly polar PFAS and the increasing significance of organic phases with increasing PFAS polarity.

The distribution of neutral compounds in biphasic separation systems can be described by the solvation parameter model using six solute properties, or descriptors. These descriptors (McGowan's characteristic volume, excess molar refraction, dipolarity/polarizability, hydrogen-bond acidity and basicity, and the gas-liquid partition constant on n-hexadecane at 298.15 K) are curated in two publicly accessible databases for hundreds (WSU compound descriptor database) or thousands (Abraham compound descriptor database). These databases were developed independently using different approaches resulting in descriptor values that vary for many compounds. Previously, it was shown that the two descriptor databases are not interchangeable, and the WSU descriptor database consistently demonstrated improved model performance for chromatographic systems where the uncertainty in the dependent variable was minimized by suitable quality control and calibration procedures. In this report we wish to evaluate whether the same conclusions are true for models with a dependent variable containing significant measurement uncertainty. To evaluate this hypothesis, we assembled databases for water-air, octanol-air, and octanol-water partition constants reported by multiple laboratories using various measurement methods. It was found that database selection has little effect on model quality or model predictive capability but significantly affects the assignment of the contribution of individual intermolecular interactions to the dependent variable. The latter information is database specific, and a quantitative comparison of system constants should be restricted to models using the same compound descriptor database., Competing Interests: Declaration of Competing Interest The author declares that he has no conflicts of interest in connection with this study., (Copyright © 2023 Elsevier B.V. All rights reserved.)

In air-breathing organisms, an organic chemical's susceptibility to elimination via urinary excretion and respiratory exhalation can be judged on the basis of the octanol-water partition ratio ( K OW ) and the octanol-air partition ratio ( K OA ), respectively. Current regulations specify that chemicals with K OW values of <10 2 and K OA values of <10 5 may be screened as non-bioaccumulative in air breathers. Here we used a model-based approach to evaluate whether these thresholds are consistent with a biomagnification factor of 1 for 141 different mammals, birds, and reptiles. Animals with lower rates of respiration (e.g., manatees and sloths) and those ingesting high-lipid diets (e.g., polar bears and carnivorous birds) were predicted to be able to biomagnify persistent chemicals with K OA values of <10 5 . This was also observed for several temperate reptiles due to their lower respiration rates and internal temperatures. Protective K OA thresholds were determined to be <10 4.85 for mammals, <10 4.60 for birds, <10 4.60 for reptiles at >25 °C, and <10 3.95 for reptiles at ≤25 °C. For all animals, urination alone was not efficient to prevent the biomagnification of any organic chemical. For chemicals with K OW values of <10 1 , we found that biomagnification of persistent chemicals was constrained by the water-air partition ratio ( K WA ) rather than K OA . Differences in physiology may need to be considered in bioaccumulation assessments of air-breathing species.

Hydrazoic acid (HN 3 ) and its deprotonated form azide ion (N 3 - ) (AHA) are toxic because they inhibit the cytochrome c oxidase complex IV (CoX IV) embedded in the inner mitochondrial membrane that forms part of the enzyme complexes involved in cellular respiration. Critical to its toxicity is the inhibition of CoX IV in the central nervous system and cardiovascular system. Hydrazoic acid is an ionizable species and its affinity for membranes, and the associated permeabilities, depend on the pH values of aqueous media on both sides of the membranes. In this article, we address the permeability of AHA through the biological membrane. In order to understand the affinity of the membrane for the neutral and ionized form of azide, we measured the octanol/water partition coefficients at pH values of 2.0 and 8.0, which are 2.01 and 0.00034, respectively. Using a Parallel Artificial Membrane Permeability Assay (PAMPA) experiment, we measured the effective permeability through the membrane, which is logP e  - 4.97 and - 5.26 for pH values of 7.4 and pH 8.0, respectively. Experimental permeability was used to validate theoretical permeability, which was estimated by numerically solving a Smoluchowski equation for AHA diffusion through the membrane. We demonstrated that the rate of permeation through the cell membrane of 8.46·10 4  s -1 is much higher than the rate of the chemical step of CoX IV inhibition by azide of 200 s -1 . The results of this study show that transport through the membrane does not represent the rate-limiting step and therefore does not control the rate of CoX IV inhibition in the mitochondria. However, the observed dynamics of azide poisoning is controlled by circulatory transport that takes place on a time scale of minutes., (© 2023. The Author(s).)

Predicting solubility of small molecules is a very difficult undertaking due to the lack of reliable and consistent experimental solubility data. It is well known that for a molecule in a crystal lattice to be dissolved, it must, first, dissociate from the lattice and then, second, be solvated. The melting point of a compound is proportional to the lattice energy, and the octanol-water partition coefficient (log P ) is a measure of the compound's solvation efficiency. The CCDC's melting point dataset of almost one hundred thousand compounds was utilized to create widely applicable machine learning models of small molecule melting points. Using the general solubility equation, the aqueous thermodynamic solubilities of the same compounds can be predicted. The global model could be easily localized by adding additional melting point measurements for a chemical series of interest.

Bioactive compounds generally need to cross membranes to arrive at their site of action. The octanol-water partition coefficient (lipophilicity, logP OW ) has proven to be an excellent proxy for membrane permeability. In modern drug discovery, logP OW and bioactivity are optimized simultaneously, for which fluorination is one of the relevant strategies. The question arises as to which extent the often subtle logP modifications resulting from different aliphatic fluorine-motif introductions also lead to concomitant membrane permeability changes, given the difference in molecular environment between octanol and (anisotropic) membranes. It was found that for a given compound class, there is excellent correlation between logP OW values with the corresponding membrane molar partitioning coefficients (logK p ); a study enabled by novel solid-state 19 F NMR MAS methodology using lipid vesicles. Our results show that the factors that cause modulation of octanol-water partition coefficients similarly affect membrane permeability., (© 2023 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

The field of cell-penetrating peptides is dominated by the use of oligomers of arginine residues. Octanol-water partitioning in the presence of an anionic lipid is a validated proxy for cell-penetrative efficacy. Here, we add one, two, or three N-methyl groups to Ac-Arg-NH 2 and examine the effects on octanol-water partitioning. In the absence of an anionic lipid, none of these arginine derivatives can be detected in the octanol layer. In the presence of sodium dodecanoate, however, increasing N-methylation correlates with increasing partitioning into octanol, which is predictive of higher cell-penetrative ability. We then evaluated fully N α -methylated oligoarginine peptides and observed an increase in their cellular penetration compared with canonical oligoarginine peptides in some contexts. These findings indicate that a simple modification, N α -methylation, can enhance the performance of cell-penetrating peptides., (© 2022 The Authors. Journal of Peptide Science published by European Peptide Society and John Wiley & Sons Ltd.)

During preclinical evaluations of drug candidates, several physicochemical (p-chem) properties are measured and employed as metrics to estimate drug efficacy in vivo. Two such p-chem properties are the octanol-water partition coefficient, Log P , and distribution coefficient, Log D , which are useful in estimating the distribution of drugs within the body. Log P and Log D are traditionally measured using the shake-flask method and high-performance liquid chromatography. However, it is challenging to measure these properties for species that are very hydrophobic (or hydrophilic) owing to the very low equilibrium concentrations partitioned into octanol (or aqueous) phases. Moreover, the shake-flask method is relatively time-consuming and can require multistep dilutions as the range of analyte concentrations can differ by several orders of magnitude. Here, we circumvent these limitations by using machine learning (ML) to correlate Log P and Log D with liquid chromatography (LC) retention time (RT). Predictive models based on four ML algorithms, which used molecular descriptors and LC RTs as features, were extensively tested and compared. The inclusion of RT as an additional descriptor improves model performance (MAE = 0.366 and R 2 = 0.89), and Shapley additive explanations analysis indicates that RT has the highest impact on model accuracy.

The octanol/air partition coefficient K oa is important for assessing the bioconcentration of airborne xenobiotics in foliage and in air-breathing organisms. Moreover, K oa informs about compound partitioning to aerosols and indoor dust, and complements the octanol/water partition coefficient K ow and the air/water partition coefficient K aw for multimedia fate modeling. Experimental log  K oa at 25 °C has been collected from literature for 2161 compounds with molecular weights from 16 to 959 Da. The curated data set covers 18.2 log units (from -1.0 to 17.2). A newly developed fragment model for predicting log  K oa from molecular structure outperforms COSMOtherm, EPI-Suite KOAWIN, OPERA, and linear solvation energy relationships (LSERs) regarding the root-mean-squared error (rms) and the maximum negative and positive errors (mne and mpe) (rms: 0.57 vs 0.86 vs 1.09 vs 1.19 vs 1.05-1.53, mne: -2.55 vs -3.95 vs -7.51 vs -7.54 vs (-5.63) - (-7.34), mpe: 2.91 vs 5.97 vs 7.54 vs 4.24 vs 6.89-10.2 log units). The prediction capability, statistical robustness, and sound mechanistic basis are demonstrated through initial separation into a training and prediction set (80:20%), mutual leave-50%-out validation, and target value scrambling in terms of temporarily wrong compound- K oa allocations. The new general-purpose model is implemented in a fully automatized form in the ChemProp software available to the public. Regarding K oa indirectly determined through K ow and K aw , a new approach is developed to convert from wet to dry octanol, enabling higher consistency in experimental (and thus also predicted) K oa .

In this study, generalized predictive models were developed to estimate K OA of four kinds of aromatic pollutants based on the calculated solvation free energy and taking the dimer effect into account. Uncorrected log K OA values, which were directly estimated from the calculated solvation free energy of individual molecules, underestimated experimental values, and the deviation increased with increasing log K OA . Dimers were found to greatly affect the apparent K OA values of these aromatic pollutants, which were driven by π-π interactions. London dispersion and exchange-repulsion terms were identified to be dominant components of the underlying π-π interactions. It is interesting to find that the π-π interactions of polybrominated diphenyl ethers correlate with not only the molecular polarizability but also the size of opposing aromatic surfaces, which leads to a different trend of π-π interactions from other aromatic pollutants. A universal quantitative structure-activity relationship model was developed to estimate the proportion of dimers based on five molecular structural descriptors relevant to the π-π interactions. After calibration with the dimer effect, estimations of log K OA were consistent with experimental values. Therefore, the dimer effect should be taken into consideration when investigating the partition behavior of aromatic pollutants, and the solvation free energy model could be an alternative method for the prediction of K OA ., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

To advance methods for bioaccumulation assessment of organic substances in air-breathing organisms, the present study developed an in vitro approach for screening neutral hydrophobic organic substances for their bioaccumulation potential in air-breathing organisms consisting of (1) depletion assays for chemicals in rat liver S9 subcellular fractions, (2) in vitro-in vivo extrapolation, and (3) whole-organism bioaccumulation modeling to assess the biomagnification potential of neutral organic substances in the rat. Testing of the in vitro method on 14 test chemicals of potentially biomagnifying substances showed that the bioassays could be conducted with a high level of reproducibility and that in vitro-derived elimination rate constants were in good agreement with in vivo-determined elimination rate constants in the rat. Exploring the potential of the in vitro approach for screening organic chemicals for bioaccumulation in air-breathing organisms indicated that chemical substances that exhibit a depletion rate constant in the S9 in vitro bioassay ≥0.3 h -1 are not expected to biomagnify in rats independent of their octanol-water partitioning coefficient (K OW ) or octanol-air partitioning coefficient (K OA ). The high level of reproducibility achieved in the test, combined with the good agreement between in vitro-derived and in vivo-determined depuration rates, suggests that the in vitro approach in combination with a K OA - and K OW -based screening approach has good potential for screening chemicals in commerce for their bioaccumulation potential in air-breathing organisms in a cost-effective and expedient manner, especially if the bioassay can be automated. Environ Toxicol Chem 2022;41:2565-2579. © 2022 SETAC., (© 2022 SETAC.)

Partition coefficients for storage lipid-water (logK lw ) and phospholipid-water (logK pw ) phases are key parameters to understand the bioaccumulation and toxicity of organic contaminants. However, the published experimental databases of these properties are dwarfs and current estimation approaches are cumbersome. Here, we present partition models that exploit the correlations of logK lw , and of logK pw with the linear combinations of the octanol-water partition coefficient (logK ow ) and the dimensionless Henry's law constant (air-water partition coefficient, logK aw ). The calibrated partition models successfully describe the variations in logK lw data (n = 305, R 2  = 0.971, root-mean-square-error (rmse) = 0.375), and in logK pw data (n = 131, R 2  = 0.953, rmse = 0.413). With the inputs of logK ow and logK aw estimated from the U.S. EPA's EPI Suite, our models of logK lw and logK pw have exhibited rmse = 0.52 with respect to experimental values indicating suitability of these models for inclusion in the EPI Suite. Our models perform similar to or better than the previously reported models such as one parameter partition models, Abraham solvation models, and models based on quantum-chemical calculations. Taken together, our models are robust, easy-to-use, and provide insight into variations of logK lw and logK pw in terms of hydrophobicity and volatility trait of chemicals., (© 2022. The Author(s).)

Because the respiration processes contributing to the elimination of organic chemicals deviate between air- and water-breathing organisms, existing and widely used procedures for identifying chemicals not subject to bioaccumulation in aquatic organisms based on the octanol-water partition ratio K OW need to be complemented with similar procedures for organisms respiring air. Here, we propose such a procedure that relies on the comparison of a compound's predicted K OW , octanol-air partition ratio K OA , and biotransformation half-life HL B with three threshold values, below which elimination is judged to be sufficiently rapid to prevent bioaccumulation. The method allows for the consideration of the effect of dissociation on the efficiency of urinary and respiratory elimination. Explicit application of different types of the prediction error, such as the 95% prediction interval or the standard error, allows for variable tolerance for false-negative decisions, that is, the potential to judge a chemical as not bioaccumulative even though it is. A test with a set of more than 1000 diverse organic chemicals confirms the applicability of the prediction methods for a wide range of compounds and the procedure's ability to categorize approximately four-fifth of compounds as being of no bioaccumulation concern, suggesting its usefulness to screen large numbers of commercial chemicals to identify those worthy of further scrutiny. The test also demonstrates that a screening based solely on K OW and K OA would be far less effective because the fraction of chemicals that can be judged as sufficiently volatile and/or sufficiently water soluble for rapid respiratory and urinary elimination based on the partitioning properties predicted for their neutral form is relatively small. Future improvements of the proposed procedure depend largely on the development of prediction methods for the biotransformation kinetics in air-breathing organisms and for the potential for renal reabsorption. Integr Environ Assess Manag 2022;18:1297-1312. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

Blind predictions of octanol/water partition coefficients and pKa at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. Octanol/water partition coefficients were predicted from solvation free energies computed using electronic structure calculations with the SM12, SM8 and SMD solvation models. Within these calculations we compared the use of gas- and solution-phase optimized geometries of the solute. Based on these calculations we found that in general the use of solution phase-optimized geometries increases the affinity of the solutes for water as compared to octanol, with the use of gas-phase optimized geometries resulting in the better agreement with experiment. The pKa is computed using the direct approach, scaled solvent-accessible surface model, and the inclusion of an explicit water molecule, where the latter two methods have previously been shown to offer improved predictions as compared to the direct approach. We find that the use of an explicit water molecule provides superior predictions, and that the predicted macroscopic pKa is sensitive to the employed microstates., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Lipophilicity can be measured with different methods, such as Shake-Flask or liquid chromatography. HPLC presents the advantage of overcoming solubility issues and therefore extending the range of lipophilicity to high values. A specific HPLC method, called ELogD, had been developed 20 years ago on a C 16 -amide stationary phase, enhancing hydrophobic and hydrogen bond interactions to mimic octanol-water partition. The emergence of novel stationary phases and the need for a less complex mobile phase have led to the development of a new HPLC assay called alphaLogD, applicable to neutral and basic compounds at pH 7.4, that combines superficially porous particles with a high number of equilibriums between solutes and stationary phase, leading to a lower number of isocratic methods to determine the logk' w at a higher throughput. Statistical studies have been run to successfully evaluate the alphaLogD method compared to the Shake-Flask method and to allow this lipophilicity measurement into the so-called Beyond-Rule-of-5-molecules space., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

In drug discovery, partition and distribution coefficients, logP and logD for octanol/water, are widely used as metrics of the lipophilicity of molecules, which in turn have a strong influence on the bioactivity and bioavailability of potential drugs. There are a variety of established methods, mostly fragment or atom-based, to calculate logP while logD prediction generally relies on calculated logP and pKa for the estimation of neutral and ionized populations at a given pH. Algorithms such as ClogP have limitations generally leading to systematic errors for chemically related molecules while pKa estimation is generally more difficult due to the interplay of electronic, inductive and conjugation effects for ionizable moieties. We propose an integrated machine learning QSAR modeling approach to predict logD by training the model with experimental data while using ClogP and pKa predicted by commercial software as model descriptors. By optimizing the loss function for the ClogD calculated by the software, we build a correction model that incorporates both descriptors from the software and available experimental logD data. Additionally, we calculate logP from the logD model using the software predicted pKa's. Here, we have trained models using publicly or commercial available logD data to show that this approach can improve on commercial software predictions of lipophilicity. When applied to other logD data sets, this approach extends the domain of applicability of logD and logP predictions over commercial software. Performance of these models favorably compare with models built with a larger set of proprietary logD data., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Efficient drug discovery is based on a concerted effort in optimizing bioactivity and compound properties such as lipophilicity, and is guided by efficiency metrics that reflect both aspects. While conformation-activity relationships and ligand conformational control are known strategies to improve bioactivity, the use of conformer-specific lipophilicities (logp) is much less explored. Here we show how conformer-specific logp values can be obtained from knowledge of the macroscopic logP value, and of the equilibrium constants between the individual species in water and in octanol. This is illustrated with fluorinated amide rotamers, with integration of rotamer 19 F NMR signals as a facile, direct method to obtain logp values. The difference between logp and logP optimization is highlighted, giving rise to a novel avenue for lipophilicity control in drug discovery., (© 2021 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

Octanol/water ( K OW ), octanol/air ( K OA ), and hexadecane/air ( K HdA ) partition coefficients are calculated for 67 organic compounds of environmental concern using computational chemistry. The extended CRENSO workflow applied here includes the calculation of extensive conformer ensembles with semiempirical methods and refinement through density functional theory, taking into account solvation models, especially COSMO-RS, and thermostatistical contributions. This approach is particularly advantageous for describing large and nonrigid molecules. With regard to K OW and K HdA , one can refer to many experimental data from direct and indirect measurement methods, and very good matches with results from our quantum chemical workflow are evident. In the case of the K OA values, however, good matches are only obtained for the experimentally determined values. Larger systematic deviations between data computed here and available, nonexperimental quantitative structure-activity relationship literature data occur in particular for phthalic acid esters and organophosphate esters. From a critical analysis of the coefficients calculated in this work and comparison with available literature data, we conclude that the presented quantum chemical composite approach is the most powerful so far for calculating reliable partition coefficients because all physical contributions to the conformational free energy are considered and the structure ensembles for the two phases are generated independently and consistently.

The octanol-air equilibrium partition ratio (K OA ) is frequently used to describe the volatility of organic chemicals, whereby n-octanol serves as a substitute for a variety of organic phases ranging from organic matter in atmospheric particles and soils, to biological tissues such as plant foliage, fat, blood, and milk, and to polymeric sorbents. Because measured K OA values exist for just over 500 compounds, most of which are nonpolar halogenated aromatics, there is a need for tools that can reliably predict this parameter for a wide range of organic molecules, ideally at different temperatures. The ability of five techniques, specifically polyparameter linear free energy relationships (ppLFERs) with either experimental or predicted solute descriptors, EPISuite's KOAWIN, COSMOtherm, and OPERA, to predict the K OA of organic substances, either at 25 °C or at any temperature, was assessed by comparison with all K OA values measured to date. In addition, three different ppLFER equations for K OA were evaluated, and a new modified equation is proposed. A technique's performance was quantified with the mean absolute error (MAE), the root mean square error (RMSE), and the estimated uncertainty of future predicted values, that is, the prediction interval. We also considered each model's applicability domain and accessibility. With an RMSE of 0.37 and a MAE of 0.23 for predictions of log K OA at 25 °C and RMSE of 0.32 and MAE of 0.21 for predictions made at any temperature, the ppLFER equation using experimental solute descriptors predicted the K OA the best. Even if solute descriptors must be predicted in the absence of experimental values, ppLFERs are the preferred method, also because they are easy to use and freely available. Environ Toxicol Chem 2021;40:3166-3180. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC., (© 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

Purpose: A linear solvation energy relationship (LSER) was developed to predict the partitioning of neutral chemicals from polysorbate 80 (PS 80) micelles to water. Predicted partition coefficients were converted to a concentration dependent solubilization strength of aqueous PS 80 solutions. This solubilization strength represents a key parameter to project equilibrium levels of leaching from pharmaceutical plastic materials., Methods: To construct the LSER model equation, partition coefficients between PS 80 micelles and water were measured via a reference phase method or collected from the literature. Multiple linear regression of partition coefficients against five publicly available solute parameters was used to obtain the LSER system parameters., Results: 112 chemically diverse compounds were incorporated for LSER model regression. The model equation shows a very good fit (R 2  = 0.969, SD = 0.219) for the entire dataset. The accuracy of the multi-parameter LSER model was proven to be substantially better in comparison to a single-parameter log-linear model based on the octanol-water partition coefficient., Conclusion: PS 80 solubilization strength in water can expediently and accurately be calculated for neutral organic compounds with the proposed LSER model. LSER system parameters provide insightful chemical information with respect to solubilization in aqueous solutions of PS 80., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

We predicted water-octanol partition coefficients for the molecules in the SAMPL7 challenge with explicit solvent classical molecular dynamics (MD) simulations. Water hydration free energies and octanol solvation free energies were calculated with a windowed alchemical free energy approach. Three commonly used force fields (AMBER GAFF, CHARMM CGenFF, OPLS-AA) were tested. Special emphasis was placed on converging all simulations, using a criterion developed for the SAMPL6 challenge. In aggregate, over 1000 [Formula: see text]s of simulations were performed, with some free energy windows remaining not fully converged even after 1 [Formula: see text]s of simulation time. Nevertheless, the amount of sampling produced [Formula: see text] estimates with a precision of 0.1 log units or better for converged simulations. Despite being probably as fully sampled as can expected and is feasible, the agreement with experiment remained modest for all force fields, with no force field performing better than 1.6 in root mean squared error. Overall, our results indicate that a large amount of sampling is necessary to produce precise [Formula: see text] predictions for the SAMPL7 compounds and that high precision does not necessarily lead to high accuracy. Thus, fundamental problems remain to be solved for physics-based [Formula: see text] predictions., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Within the scope of SAMPL7 challenge for predicting physical properties, the Integral Equation Formalism of the Miertus-Scrocco-Tomasi (IEFPCM/MST) continuum solvation model has been used for the blind prediction of n-octanol/water partition coefficients and acidity constants of a set of 22 and 20 sulfonamide-containing compounds, respectively. The log P and pK a were computed using the B3LPYP/6-31G(d) parametrized version of the IEFPCM/MST model. The performance of our method for partition coefficients yielded a root-mean square error of 1.03 (log P units), placing this method among the most accurate theoretical approaches in the comparison with both globally (rank 8th) and physical (rank 2nd) methods. On the other hand, the deviation between predicted and experimental pK a values was 1.32 log units, obtaining the second best-ranked submission. Though this highlights the reliability of the IEFPCM/MST model for predicting the partitioning and the acid dissociation constant of drug-like compounds compound, the results are discussed to identify potential weaknesses and improve the performance of the method., (© 2021. The Author(s).)

Partition coefficients quantify a molecule's distribution between two immiscible liquid phases. While there are many methods to compute them, there is not yet a method based on the free energy of each system in terms of energy and entropy, where entropy depends on the probability distribution of all quantum states of the system. Here we test a method in this class called Energy Entropy Multiscale Cell Correlation (EE-MCC) for the calculation of octanol-water logP values for 22 N-acyl sulfonamides in the SAMPL7 Physical Properties Challenge (Statistical Assessment of the Modelling of Proteins and Ligands). EE-MCC logP values have a mean error of 1.8 logP units versus experiment and a standard error of the mean of 1.0 logP units for three separate calculations. These errors are primarily due to getting sufficiently converged energies to give accurate differences of large numbers, particularly for the large-molecule solvent octanol. However, this is also an issue for entropy, and approximations in the force field and MCC theory also contribute to the error. Unique to MCC is that it explains the entropy contributions over all the degrees of freedom of all molecules in the system. A gain in orientational entropy of water is the main favourable entropic contribution, supported by small gains in solute vibrational and orientational entropy but offset by unfavourable changes in the orientational entropy of octanol, the vibrational entropy of both solvents, and the positional and conformational entropy of the solute., (© 2021. The Author(s).)

The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. The SAMPL7 physical property challenge dealt with prediction of octanol-water partition coefficients and pK a for 22 compounds. The dataset was composed of a series of N-acylsulfonamides and related bioisosteres. 17 research groups participated in the log P challenge, submitting 33 blind submissions total. For the pK a challenge, 7 different groups participated, submitting 9 blind submissions in total. Overall, the accuracy of octanol-water log P predictions in the SAMPL7 challenge was lower than octanol-water log P predictions in SAMPL6, likely due to a more diverse dataset. Compared to the SAMPL6 pK a challenge, accuracy remains unchanged in SAMPL7. Interestingly, here, though macroscopic pK a values were often predicted with reasonable accuracy, there was dramatically more disagreement among participants as to which microscopic transitions produced these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pK a prediction methods., (© 2021. The Author(s).)

Vector control and personal protection against anthropophilic mosquitoes mainly rely on the use of insecticides and repellents. The search for mosquito-attractive semiochemicals has been the subject of intense studies for decades, and new compounds or odor blends are regularly proposed as lures for odor-baited traps. We present a comprehensive and up-to-date review of all the studies that have evaluated the attractiveness of volatiles to mosquitoes, including individual chemical compounds, synthetic blends of compounds, or natural host or plant odors. A total of 388 studies were analysed, and our survey highlights the existence of 105 attractants (77 volatile compounds, 17 organism odors, and 11 synthetic blends) that have been proved effective in attracting one or several mosquito species. The exhaustive list of these attractants is presented in various tables, while the most common mosquito attractants - for which effective attractiveness has been demonstrated in numerous studies - are discussed throughout the text. The increasing knowledge on compounds attractive to mosquitoes may now serve as the basis for complementary vector control strategies, such as those involving lure-and-kill traps, or the development of mass trapping. This review also points out the necessity of further improving the search for new volatile attractants, such as new compound blends in specific ratios, considering that mosquito attraction to odors may vary over the life of the mosquito or among species. Finally, the use of mosquito attractants will undoubtedly have an increasingly important role to play in future integrated vector management programs.

Olfaction is orchestrated at different stages and involves various proteins at each step. For example, odorant-binding proteins (OBPs) are soluble proteins found in sensillum lymph that might encounter odorants before reaching the odorant receptors. In tsetse flies, the function of OBPs in olfaction is less understood. Here, we investigated the role of OBPs in Glossina fuscipes fuscipes olfaction, the main vector of sleeping sickness, using multidisciplinary approaches. Our tissue expression study demonstrated that GffLush was conserved in legs and antenna in both sexes, whereas GffObp44 and GffObp69 were expressed in the legs but absent in the antenna. GffObp99 was absent in the female antenna but expressed in the male antenna. Short odorant exposure induced a fast alteration in the transcription of OBP genes. Furthermore, we successfully silenced a specific OBP expressed in the antenna via dsRNAi feeding to decipher its function. We found that silencing OBPs that interact with 1-octen-3-ol significantly abolished flies' attraction to 1-octen-3-ol, a known attractant for tsetse fly. However, OBPs that demonstrated a weak interaction with 1-octen-3-ol did not affect the behavioral response, even though it was successfully silenced. Thus, OBPs' selective interaction with ligands, their expression in the antenna and their significant impact on behavior when silenced demonstrated their direct involvement in olfaction.

Herein I present a review on the synthesis of ipsenol and ipsdienol, two aggregation pheromones of bark beetles, isolated from different species of genus Ips, and serious pests of conifer forests. I have covered the literature for around fifty years, since 1968 to 2020. This account has been divided in different sections and sub-sections, including a general and brief outlook on their isolation, structure and biological activity, to continue with the reported synthesis of racemic ipsenol and ipsdienol, including my own contribution to topic, and the presentation of reports describing the synthesis of enantiomerically pure ipsenol and ipsdienol. Particular attention has been devoted to identify and highlight racemic or enantiomerically pure "isoprene synthons", and isoprenylation methods employed in the synthesis of ipsenol and ipsdienol, of general interest for related terpene derivatives synthesis., (© 2021 The Chemical Society of Japan & Wiley-VCH GmbH.)

The existing information supports the use of this material as described in this safety assessment. 3-Octanol was evaluated for genotoxicity, repeated dose toxicity, reproductive toxicity, local respiratory toxicity, phototoxicity/photoallergenicity, skin sensitization, and environmental safety. Data from read-across analog 3-hexanol (CAS # 623-37-0) show that 3-octanol is not expected to be genotoxic. Data on 3-octanol provide a calculated margin of exposure (MOE) > 100 for the repeated dose toxicity endpoint. Data on read-across analog 2-octanol (CAS # 123-96-6) provide a calculated MOE >100 for the reproductive toxicity endpoint and show that there are no safety concerns for skin sensitization under the current declared levels of use. The phototoxicity/photoallergenicity endpoints were evaluated based on ultraviolet (UV) spectra; 3-octanol is not expected to be phototoxic/photoallergenic. The local respiratory toxicity endpoint was evaluated using the Threshold of Toxicological Concern (TTC) for a Cramer Class I material; exposure is below the TTC (1.4 mg/day). The environmental endpoints were evaluated; 3-octanol was found not to be Persistent, Bioaccumulative, and Toxic (PBT) as per the International Fragrance Association (IFRA) Environmental Standards, and its risk quotients, based on its current volume of use in Europe and North America (i.e., Predicted Environmental Concentration/Predicted No Effect Concentration [PEC/PNEC]), are <1., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Octanol-water partition coefficient (logK ow ) and soil organic carbon content normalized sorption coefficient (logK oc ) values are two important physicochemical properties in the context of bioaccumulation and environmental fate of organic compounds and their environmental risk assessment. Simple, interpretable and easy-to-derive extended topochemical atom (ETA) indices obtained from 2D structural representation of compounds were used for quantitative structure-property relationship (QSPR) modeling of these two endpoints. Linear regression based models developed using only ETA indices show encouraging statistical and validation results. Based on the information obtained from developed QSPR models, we may conclude that molecular volume, branching pattern, presence of hydrophobic Cl atoms, cyclicity/fusion, polar environment, electron density, unsaturation content, hydrogen bonding propensity or hydrogen bond donor atoms, local topology, presence of heteroatoms and aromaticity are crucial factors in controlling the logK ow and logK oc values of the compounds. The suggested explanatory features for different classes of chemicals or the whole diverse set can help in safer designing of chemicals, which is one of the primary agenda of the "Green Chemistry" program., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Giant Unilamellar Vesicles (GUVs) are a versatile tool in many branches of science, including biophysics and synthetic biology. Octanol-Assisted Liposome Assembly (OLA), a recently developed microfluidic technique enables the production and testing of GUVs within a single device under highly controlled experimental conditions. It is therefore gaining significant interest as a platform for use in drug discovery, the production of artificial cells and more generally for controlled studies of the properties of lipid membranes. In this work, we expand the capabilities of the OLA technique by forming GUVs of tunable binary lipid mixtures of DOPC, DOPG and DOPE. Using fluorescence recovery after photobleaching we investigated the lateral diffusion coefficients of lipids in OLA liposomes and found the expected values in the range of 1 μm 2 /s for the lipid systems tested. We studied the OLA derived GUVs under a range of conditions and compared the results with electroformed vesicles. Overall, we found the lateral diffusion coefficients of lipids in vesicles obtained with OLA to be quantitatively similar to those in vesicles obtained via traditional electroformation. Our results provide a quantitative biophysical validation of the quality of OLA derived GUVs, which will facilitate the wider use of this versatile platform., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

This study is directed toward assessing the predictive potential of eigenvalue-based topological molecular descriptors. The graph energy, Estrada index, resolvent energy, and the Laplacian energy were tested as parameters for the prediction of boiling points, heats of formation, and octanol/water partition coefficients of alkanes. It was shown that an eigenvalue-based molecular descriptor cannot be individually used for successful prediction of these physico-chemical properties, but the first Zagreb index, the number of zeros in the spectrum and the number of methyl groups must be also involved in the models. Performed statistics show that the models constructed using the Estrada index and resolvent energy are significantly better than ones with the energy of a graph and the Laplacian energy. Such a trend is even more noticeable in the case of octanol/water partition coefficients of alkanes.

Molecular separation of pharmaceutical contaminants from water has been recently of great interest to alleviate their detrimental impacts on environment and human well-being. As the novelty, this investigation aims to develop a mechanistic modeling approach and consequently its related CFD-based simulations to evaluate the molecular separation efficiency of ibuprofen (IP) and its metabolite 4-isobutylacetophenone (4-IBAP) from water inside a porous membrane contactor (PMC). For this purpose, octanol has been applied as an organic phase to extract IP and 4-IBAP from the aqueous solution due to high solubility of solutes in octanol. Finite element (FE) technique is used as a promising tool to simultaneously solve continuity and Navier-Stokes equations and their associated boundary conditions in tube, shell and porous membrane compartments of the PMC. The results demonstrated that the application of PMC and liquid-liquid extraction process can be significantly effective due to separating 51 and 54% of inlet IP and 4-IBAP molecules from aqueous solution, respectively. Moreover, the impact of various operational / functional parameters such as packing density, the number of fibrous membrane, the module length, the membrane porosity / tortuosity, and ultimately the aqueous solution flow rate on the molecular separation efficiency of IP and 4-IBAP is studied in more details., Competing Interests: The authors have declared that no competing interests exist.

The physicochemical properties of small molecules that can be determined by retention measurements in reversed-phase liquid chromatography include solvent-based properties inferred from equilibrium processes occurring predominantly in the mobile phase and sorption properties for materials which can be used as stationary phases inferred from solute-stationary phase interactions. In addition, physicochemical properties can be estimated from correlation models based on surrogate chromatographic systems with a similar capability for intermolecular interactions to the chemical or biological system. Examples of properties determined by direct methods include molecular descriptors (solvation parameter model), acid dissociation constants, formation constants, and surface properties of solids determined by inverse liquid chromatography. Examples of properties estimated by indirect methods include hydrophobicity, lipophilicity, n-octanol-water partition constant, soil-water sorption constant, non-specific toxicity to fish and microorganisms, and permeation coefficients for the blood-brain and skin-water barriers. Since all approaches depend on an accurate measurement of chromatographic retention parameters typical operational and mechanistic problems are discussed from the perspective of data quality. Fundamentally the accuracy of direct methods is limited by stationary phase heterogeneity and indirect methods by the limited number of suitable surrogate chromatographic models., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest in connection with this study., (Copyright © 2020 Elsevier B.V. All rights reserved.)

In the present study, 88 structurally- diverse drugs were investigated by biopartitioning micellar chromatography (BMC) using Brij-35 as surfactant under different chromatographic conditions. It was found that temperature and presence of NaCl have only a minor effect in BMC retention. Correlation of BMC retention factors with octanol-water partitioning required the inclusion of fractions of ionized species as additional parameters, showing that there is a weaker effect of ionization in BMC environment. Compared to Immobilized Artificial Membrane (IAM) Chromatography, BMC retention factors cover a relatively narrow span, two-fold smaller than retention factors on IAM stationary phases as a result of the presence of micelles facilitating elution of lipophilic compounds and the absence of secondary attractive electrostatic interactions in the BMC environment. Similarities/dissimilarities between BMC, octanol-water partitioning and IAM Chromatography were investigated by Linear Free Energy Relationships (LSER). BMC retention factors were used to construct relationships with cell permeability,% Human Oral Absorption (%HOA) and Plasma Protein Binding (%PPB). Linear BMC models were obtained with Caco-2 cell lines and Parallel Artificial Membrane Permeability Assay (PAMPA). For %HOA, a hyperbolic model was established upon incorporation of topological polar surface area (tPSA) as additional parameter. A sigmoidal model was constructed for %PPB and a linear one for the corresponding thermodynamic binding constant logK. In both cases inclusion of the fraction of anionic species with a positive sign was required reflecting the preference of human albumin for acidic drugs., (Copyright © 2020. Published by Elsevier B.V.)

The soil-air exchange of pesticides is one potential fate and exposure pathways, and this process is generally thought to be governed by soil properties and environmental conditions. The experimental determination of soil-air partitioning coefficient (Ksa) is laborious and costly and typically, Ksa's are predicted from a semiempirical or a simple linear regression approach with soil and environmental variables. Here we developed a model that combined linear regression of soil, environmental and molecular parameters with the quantitative structural-property relationship (QSPR) to predict Ksa for pesticides. The values of theoretical descriptors of pesticides were calculated and the best descriptors selected using the Boruta Algorithm. Seventy-six experimental logKsa values for 17 pesticides were used in model development. Multiple linear regression (MLR) with a soil (organic carbon fraction), physicochemical (octanol-air partitioning coefficient), environmental (temperature and humidity) and molecular descriptor (Gmin, a 2D E-state molecular parameter), called as MLR-QSPR combined model exhibited better predictability (adj. r 2  = 0.95) of logKsa compared to MLR (adj. r 2  = 0.87) or QSPR (adj. r 2  = 0.82) itself. MLR-QSPR also showed the best performance in five-fold cross-validation (adj. r 2  = 0.94) and test set verification (adj. r 2  = 0.96). The developed model was validated and characterized by the applicability domain. Results showed that the proposed MLR-QSPR approach is highly predictive and statistically robust with >95% of predictions within ±0.5 log unit of the measured Ksa. Therefore, this approach can be used in estimating the soil-air partitioning of pesticides to better predict it's fate and transport in environments., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Theoretical approaches for predicting physicochemical properties are valuable tools for accelerating the drug discovery process. In this work, quantum chemical methods are used to predict water-octanol partition coefficients as a part of the SAMPL6 blind challenge. The SMD continuum solvent model was employed with MP2 and eight DFT functionals in conjunction with correlation consistent basis sets to determine the water-octanol transfer free energy. Several tactics towards improving the predictions of the partition coefficient were examined, including increasing the quality of basis sets, considering tautomerization, and accounting for inhomogeneities in the water and n-octanol phases. Evaluation of these various schemes highlights the impact of modeling approaches across different methods. With the inclusion of tautomers and adjustments to the permittivity constants, the best predictions were obtained with smaller basis sets and the O3LYP functional, which yielded an RMSE of 0.79 logP units. The results presented correspond to the SAMPL6 logP submission IDs: DYXBT, O7DJK, and AHMTF.

Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm of partition coefficient (logP) has been developed using molecular fingerprints and a deep neural network. The machine learning model was trained on a dataset of 12,000 molecules and tested on 2000 molecules. In this article, we present our results for the blind prediction of logP for the SAMPL6 challenge. While the best submission achieved a RMSE of 0.41 logP units, our submission had a RMSE of 0.61 logP units. Overall, we ranked in the top quarter out of the 92 submissions that were made. Our results show that the deep learning model can be used as a fast, accurate and robust method for high throughput prediction of logP of small molecules.

Accurately computing partition coefficients is a pivotal part of drug discovery. Specifically, octanol-water partition coefficients can provide information into hydrophobicity of drug-like molecules, as well as a de facto representation of membrane permeability. However, one challenge facing the computation of partition coefficients is the need to encapsulate various microscopic environments. These include areas of largely bulk solvent (i.e., either water or octanol) or regions where octanol is saturated with water or areas of higher salt concentration. Also, tautomeric effects require consideration. Thus, we present a Boltzmann weighting approach that incorporates transfer free energies across varying microscopic media, as well as varying tautomeric state, to compute partition coefficients in the SAMPL6 challenge.