The chemical interpretation and practice of linear solvation energy relationships in chromatography

Streamlining Linear Free Energy Relationships of Proteins through Dimensionality Analysis and Linear Modeling

Linear free energy relationships (LFERs) are pivotal in predicting protein-water partition coefficients, with traditional one-parameter (1p-LFER) models often based on octanol. However, their limited scope has prompted a shift toward the more comprehensive but parameter-intensive Abraham solvation-based poly-parameter (pp-LFER) approach. This study introduces a two-parameter (2p-LFER) model, aiming to balance simplicity and predictive accuracy. We showed that the complex six-dimensional intermolecular interaction space, defined by the six Abraham solute descriptors, can be efficiently simplified into two key dimensions. These dimensions are effectively represented by the octanol-water (log Kow) and air-water (log Kaw) partition coefficients. Our 2p-LFER model, utilizing linear combinations of log Kow and log Kaw, showed promising results. It accurately predicted structural protein-water (log Kpw) and bovine serum albumin-water (log KBSA) partition coefficients, with R2 values of 0.878 and 0.760 and root mean squared errors (RMSEs) of 0.334 and 0.422, respectively. Additionally, the 2p-LFER model favorably compares with pp-LFER predictions for neutral per- and polyfluoroalkyl substances. In a multiphase partitioning model parametrized with 2p-LFER-derived coefficients, we observed close alignment with experimental in vivo and in vitro distribution data for diverse mammalian tissues/organs (n = 137, RMSE = 0.44 log unit) and milk-water partitioning data (n = 108, RMSE = 0.29 log units). The performance of the 2p-LFER is comparable to pp-LFER and significantly surpasses 1p-LFER. Our findings highlight the utility of the 2p-LFER model in estimating chemical partitioning to proteins based on hydrophobicity, volatility, and solubility, offering a viable alternative in scenarios where pp-LFER descriptors are unavailable.

Predicting biophysical properties of small molecules from chromatographic measurements and the solvation parameter model

Biopartitioning processes are challenging to study and often require the sacrifice of multiple animals. Therefore, it is more practical and cost-effective to correlate these processes with easily determined properties, such as chromatographic retention data, or to make predictions based on structural descriptors such as quantitative structure-property relationships or linear free energy relationships. Abraham's solvation parameter model uses six solute properties to characterize the interactions responsible for the transfer of neutral compounds between immiscible phases in chromatographic or biological systems. This review discusses the prediction of biological properties of small molecules from chromatographic measurements and the solvation parameter model. It covers the characteristics of solute descriptors in the solvation parameter model, as well as experimental approaches for their determination. Additionally, it explores recent applications of the solvation parameter model in characterizing biological systems and its use in identifying surrogate chromatographic models for predicting biological properties.

Preparation of ionic gel-modified stationary phase for RPLC/HILIC/IC separation and its application in per aqueous liquid chromatography

In this study, we synthesized and employed an ionic gel-functionalized silica stationary phase for high-performance liquid chromatography. The successful fabrication of the stationary phase was confirmed through attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), zeta-potential measurements, and elemental analysis (EA). Comparative performance evaluation against a commercial column demonstrated the prepared column's effectiveness in the mixed mode of reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), and ion chromatography (IC). Moreover, the stationary phase exhibited exceptional retention repeatability in per aqueous liquid chromatography, showcasing its potential as an environmentally friendly analytical method. Mechanistic investigations unveiled multiple solute-stationary phase interactions, including π-π interactions, hydrogen bonding, and ion exchange. Finally, we applied the developed stationary phase for the precise detection of preservatives in carbonated beverages and jelly, achieving high levels of accuracy and recovery rates.

Improved hydrophobic subtraction model of reversed-phase liquid chromatography selectivity based on a large dataset with a focus on isomer selectivity

Reversed-phase (RP) liquid chromatography is an important tool for the characterization of materials and products in the pharmaceutical industry. Method development is still challenging in this application space, particularly when dealing with closely-related compounds. Models of chromatographic selectivity are useful for predicting which columns out of the hundreds that are available are likely to have very similar, or different, selectivity for the application at hand. The hydrophobic subtraction model (HSM1) has been widely employed for this purpose; the column database for this model currently stands at 750 columns. In previous work we explored a refinement of the original HSM1 (HSM2) and found that increasing the size of the dataset used to train the model dramatically reduced the number of gross errors in predictions of selectivity made using the model. In this paper we describe further work in this direction (HSM3), this time based on a much larger solute set (1014 solute/stationary phase combinations) containing selectivities for compounds covering a broader range of physicochemical properties compared to HSM1. The molecular weight range was doubled, and the range of the logarithm of the octanol/water partition coefficients was increased slightly. The number of active pharmaceutical ingredients and related synthetic intermediates and impurities was increased from four to 28, and ten pairs of closely related structures (e.g., geometric and cis-/trans- isomers) were included. The HSM3 model is based on retention measurements for 75 compounds using 13 RP stationary phases and a mobile phase of 40/60 acetonitrile/25 mM ammonium formate buffer at pH 3.2. This data-driven model produced predictions of ln α (chromatographic selectivity using ethylbenzene as the reference compound) with average absolute errors of approximately 0.033, which corresponds to errors in α of about 3 %. In some cases, the prediction of the trans-/cis- selectivities for positional and geometric isomers was relatively accurate, and the driving forces for the observed selectivity could be inferred by examination of the relative magnitudes of the terms in the HSM3 model. For some geometric isomer pairs the interactions mainly responsible for the observed selectivities could not be rationalized due to large uncertainties for particular terms in the model. This suggests that more work is needed in the future to explore other HSM-type models and continue expanding the training dataset in order to continue improving the predictive accuracy of these models. Additionally, we release with this paper a much larger data set (43,329 total retention measurements) at multiple mobile phase compositions, to enable other researchers to pursue their own lines of inquiry related to RP selectivity.

Guidelines for descriptor assignments for the solvation parameter model by separation techniques

The solvation parameter model uses six compound descriptors to model equilibrium properties in biphasic systems formally defined as excess molar refraction, E, dipolarity/polarizability, S, overall hydrogen-bond acidity, A, overall hydrogen-bond basicity, B, McGowan's characteristic volume, V, and the gas-liquid partition constant on hexadecane at 25 °C, L. The V descriptor can be assigned from structure and the E descriptor for compounds liquid at 20 °C can be calculated from its refractive index and characteristic volume. The E descriptor for compounds solid at 20 °C and the S, A, B, and L descriptors are assigned from experimental properties traditionally obtained by chromatographic, liquid-liquid partition, and solubility measurements. Here I report an efficient experimental design using the Solver method for the accurate assignment of descriptors for neutral compounds that simultaneously minimizes laboratory resources. This multi-technique approach requires 3 retention factor measurements in a 60 °C temperature range per compound on four columns by gas chromatography, 3 retention factor measurements in a 30 % (v/v) acetonitrile composition range per compound on two columns by reversed-phase liquid chromatography, and eight partition constant measurements by liquid-liquid partition in totally organic and aqueous biphasic systems for a total of 26 experimental measurements. The accuracy of the descriptor assignments was validated by comparison with the values in the Wayne State University (WSU) descriptor database taken as the best estimate of the true descriptor values. The E, S, A, B and L descriptors were assigned simultaneously by the Solver method using the above approach without significant bias and with an average absolute deviation (AAD) of 0.054, 0.018, 0.015, 0.013, and 0.040, respectively, compared with the WSU database values, corresponding to a relative absolute average deviation in percent (RAAD) of 7.2, 1.9, 3.6, 5.1, and 0.84 %, respectively, for 32 varied compounds. This streamlined approach represents a significant improvement on earlier single-technique approaches used as the starting point for the development of the multi-technique approach. For compounds of variable hydrogen-bond basicity modifications to the multi-technique approach were implemented while maintaining the same number of experimental measurements. Acceptable descriptor assignments for B/B° were obtained for compounds liquid at 20 °C for which the E descriptor was available by calculation. For solid compounds at 20 °C the E and B/B° descriptors are restricted to qualitative application where approximate values may be acceptable.

An improved subtraction model applied in supercritical fluid chromatography to characterise polar stationary phases

Herein, an improved subtraction model was proposed to characterise the polar stationary phases in supercritical fluid chromatography (SFC). Fifteen stationary phases were selected, including two types of aromatic columns, Waters Torus and Viridis series columns, as well as silica and amino columns. Ethylbenzene and Torus 1-AA were defined as the reference solute and column, respectively. Identifying the interaction with the maximum contribution to retention in SFC separation and using it as the initial term is a key step in modelling. The dipole, or induced dipole interaction (θ'P), replaced the hydrophobic interaction (η'H) as the starting term. The improved model was expressed as logα=η'H+β'A+α'B+κ'C+θ'P+ε'E+σ'S, where the term ε'E indicated that anion exchange interaction was intentionally supplemented. A 7-step modelling process, including bidirectional fitting and residual analysis, was proposed. The obtained column parameters had reasonable physical significance, with the adjusted determination coefficient (R2adj) greater than 0.999 and the standard error (SE) less than 0.029. Methodological validation was further performed using the other four columns and 12 solutes that were not involved in the modelling. The result revealed good predictions of solutes' retention, as demonstrated by R2adj from 0.9923 to 0.9979 and SE from 0.0636 to 0.1088. This study indicated the feasibility of using the improved subtraction model to characterise polar stationary phases in SFC, with the most crucial being the determination of an initial term, followed by the addition of a new descriptor and the selection of an appropriate reference column. The study expanded the application scope of the subtraction model in SFC, which will help gain an in-depth understanding of the SFC separation mechanism.

Evaluation of the Goss-modified solvation parameter model for the characterization of biphasic systems and descriptor assignments

The solvation parameter model uses six descriptors identified as excess molar refraction, E, dipolarity/polarizability, S, overall hydrogen-bond acidity, A, overall hydrogen-bond basicity, B, McGowan's characteristic volume, V, and the gas-liquid partition constant on hexadecane at 25 °C, L to model the distribution of neutral compounds in biphasic systems. Abraham's version of this model uses all six descriptors with two separate linear free energy relationship models for the transfer of compounds from a gas phase to a condensed phase and between condensed phases. Goss proposed a modification to this model that uses a single calibration model regardless of the physical state for each phase and five of the descriptors employed in Abraham's model (E descriptor is eliminated). The capability of Abraham's model and the Goss-modified model to characterize the contribution of intermolecular interaction to retention for gas and reversed-phase liquid chromatographic systems and distribution in liquid-liquid partition systems is evaluated using the WSU compound descriptor database. These more accurate values for the Abraham descriptors have not been utilized previously for the evaluation of the Goss-modified model and should be more capable of discerning subtle differences in model performance. It is shown that model quality defined by statistical parameters favors Abraham's model over the Goss-modified model with differences in model quality greater for systems in which Abraham's model indicates a significant contribution from electron lone pair interactions and for systems in which one phase is a solvent containing perfluoroalkyl substituents. There is a small systematic difference for the terms describing the combined contributions of cavity formation and dispersion interactions and for interactions of a dipole-type. The contribution of hydrogen-bonding interactions is virtually identical for the two models. The model intercepts are generally different and potentially assigned to a larger contribution from lack-of-fit for the Goss-modified model. Although the Abraham model descriptors have been routinely employed for applications using the Goss-modified model the possibility that Goss-model specific descriptors should be employed was evaluated. Using the Solver method and Goss-model specific calibration models for chromatographic and liquid-liquid partition systems a new set of Goss-specific descriptors was calculated for 28 varied compounds. These descriptors show good statistical agreement with the Abraham descriptor values with an average deviation of 0.009, -0.003, -0.004, and -0.023, respectively, for the S, A, B, and L descriptors, corresponding to a relative absolute deviation in percent of 2.2 %, 3.9 %, 4.3 %, and 1.2 %, respectively.

Hydrogen-Bond Acidic Materials in Acoustic Wave Sensors for Nerve Chemical Warfare Agents' Detection

The latest trends in the field of the on-site detection of chemical warfare agents (CWAs) involve increasing the availability of point detectors to enhance the operational awareness of commanders and soldiers. Among the intensively developed concepts aimed at meeting these requirements, wearable detectors, gas analyzers as equipment for micro- and mini-class unmanned aerial vehicles (UAVs), and distributed sensor networks can be mentioned. One of the analytical techniques well suited for use in this field is surface acoustic wave sensors, which can be utilized to construct lightweight, inexpensive, and undemanding gas analyzers for detecting CWAs. This review focuses on the intensively researched and developed variant of this technique, utilizing absorptive sensor layers dedicated for nerve CWAs' detection. The paper describes the mechanism of the specific interaction occurring between the target analyte and the sensing layer, which serves as the foundation for their selective detection. The main section of this paper includes a chronological review of individual achievements in the field, largely based on the peer-reviewed scientific literature dating back to the mid-1980s to the present day. The final section presents conclusions regarding the prospects for the development of this analytical technique in the targeted application.

Determination of solvation parameter model compound descriptors by gas chromatography

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 the gas-liquid partition constant at 25 °C on n-hexadecane, L, to model transfer properties in gas-condensed phase biphasic systems. The E descriptor for compounds liquid at 20 °C is available by calculation using a refractive index value while E for solid compounds at 20 °C and the S, A, B, and L descriptors are determined by experiment. As a single-technique approach, it is shown that with up to 20 retention factor measurements on four columns comprising a poly(siloxane) containing methyloctyl or dimethyldiphenylsiloxane monomers (SPB-Octyl or HP-5), a poly(siloxane) containing methyltrifluoropropylsiloxane monomers (Rtx-OPP or DB-210), a poly(siloxane) containing bis(cyanopropylsiloxane) monomers (HP-88 or SGE BPX-90), and a poly(ethylene glycol) stationary phase (DB-WAXetr or HP-INNOWAX) are suitable for assigning the S, A, and L descriptors. Using the descriptors in the updated WSU compound descriptor database as target values the average absolute error in the descriptor assignments for 52 varied compounds in the temperature range 60-140 °C was 0.072 for E, 0.016 for S, 0.008 for A, and 0.022 for L corresponding to 30 %, 3.5 %, and 0.6 % as a relative average absolute error for E, S, and L, respectively. For the higher temperature range of 160-240 °C and 34 varied compounds that are liquid at 20 °C the average absolute error for the S, A and L descriptors was 0.026, 0.020, and 0.031, respectively, with the largest relative average absolute error for S of 3.2 % (< 1 % for the L descriptor). For 35 varied compounds that are solid at 20 °C the relative absolute error for the E, S, A, and L descriptors in the higher temperature range was 0.068, 0.035, 0.020, and 0.020, respectively, with a relative average absolute error for E (6.5 %), S (3.5 %) and L (0.88 %). The S, A, and L descriptor can be accurately assigned on the four-column system over a wide temperature range. The E descriptor for solid compounds at 20 °C exhibits greater variability than desirable. The B descriptor cannot be assigned by the four-column system, which lack hydrogen-bond acid functional groups, and is only poorly assigned on the weak hydrogen-bond acid ionic liquid column SLB-IL100.

Determination of the hydrogen-bond basicity descriptor by reversed-phase liquid chromatography

Except for alkanes, most organic compounds are hydrogen-bond bases. The B° descriptor of the solvation parameter model provides a convenient measure of the effective (or summation) hydrogen-bond basicity of organic compounds. A fast and convenient method to assign the B° descriptor is required to support studies of hydrogen-bonding in separation systems. A two-column system with acetonitrile-water mobile phase compositions and the measurement of up to eleven isocratic retention factors is proposed for this purpose. Several reversed-phase column chemistries and mobile phases were evaluated with the two-column system consisting of a pentafluorophenylpropylsiloxane-bonded and octadecylsiloxane-bonded silica columns recommended for this purpose. To assess the accuracy of the method values for B° were taken from the Wayne State University (WSU) compound descriptor database, which were assigned using conventional multi-technique methods and large datasets. The two-column systems provided an unbiased assignment of B° with an average deviation of 0.008 and an average absolute deviation of 0.021 compared with the target value for 55 varied compounds. The two-column system is unsuitable for assigning the other descriptors used in the solvation parameter model and results in erroneous assignments of B° for nitrogen-containing compounds capable of electrostatic interactions on silica-based reversed-phase columns.

Determination of descriptors for the principal flavor compounds of the cinnamons of commerce by gas chromatography and liquid-liquid partition

Descriptors for fourteen semivolatile organic compounds associated with the authenticity, botanical origin, and flavor potential of the cinnamons of commerce were determined using the Solver method and experimental retention factors determined by gas chromatography at several temperatures on a minimum of seven selectivity-selected, open-tubular columns and liquid-liquid partition constants in up to twenty totally organic biphasic systems. The six descriptors that encode the solvation properties of the compounds were used to predict water-gas, octanol-gas, and octanol-water partition constants commonly employed to assess environmental distribution properties. For octanol-water partition constants, log KOW, the predicted partition constants exhibited an average absolute deviation of 0.12 for log KOW experimental - log KOW predicted (n = 14). Soil-water, soil-air, urban aerosol-air, skin-water permeation, and non-specific toxicity to the fathead minnow were predicted for the same compounds to assess their potential environmental impact. The product terms of the solvation parameter model provide a useful insight into the contribution of individual intermolecular interactions to the distribution properties of the cinnamon compounds and their environmental impact.

A perspective on the use of deep deterministic policy gradient reinforcement learning for retention time modeling in reversed-phase liquid chromatography

Artificial intelligence and machine learning techniques are increasingly used for different tasks related to method development in liquid chromatography. In this study, the possibilities of a reinforcement learning algorithm, more specifically a deep deterministic policy gradient algorithm, are evaluated for the selection of scouting runs for retention time modeling. As a theoretical exercise, it is investigated whether such an algorithm can be trained to select scouting runs for any compound of interest allowing to retrieve its correct retention parameters for the three-parameter Neue-Kuss retention model. It is observed that three scouting runs are generally sufficient to retrieve the retention parameters with an accuracy (mean relative percentage error MRPE) of 1 % or less. When given the opportunity to select additional scouting runs, this does not lead to a significantly improved accuracy. It is also observed that the agent tends to give preference to isocratic scouting runs for retention time modeling, and is only motivated towards selecting gradient scouting runs when penalized (strongly) for large analysis/gradient times. This seems to reinforce the general power and usefulness of isocratic scouting runs for retention time modeling. Finally, the best results (lowest MRPE) are obtained when the agent manages to retrieve retention time data for % ACN at elution of the compound under consideration that spread the entire relevant range of ACN (5 % ACN to 95 % ACN) as well as possible, i.e., resulting in retention data at a low, intermediate and high % ACN. Based on the obtained results, we believe reinforcement learning holds great potential to automate and rationalize method development in liquid chromatography in the future.

Novel Models for Accurate Estimation of Air-Blood Partitioning: Applications to Individual Compounds and Complex Mixtures of Neutral Organic Compounds

The air-blood partition coefficient (Kab) is extensively employed in human health risk assessment for chemical exposure. However, current Kab estimation approaches either require an extensive number of parameters or lack precision. In this study, we present two novel and parsimonious models to accurately estimate Kab values for individual neutral organic compounds, as well as their complex mixtures. The first model, termed the GC×GC model, was developed based on the retention times of nonpolar chemical analytes on comprehensive two-dimensional gas chromatography (GC×GC). This model is unique in its ability to estimate the Kab values for complex mixtures of nonpolar organic chemicals. The GC×GC model successfully accounted for the Kab variance (R2 = 0.97) and demonstrated strong prediction power (RMSE = 0.31 log unit) for an independent set of nonpolar chemical analytes. Overall, the GC×GC model can be used to estimate Kab values for complex mixtures of neutral organic compounds. The second model, termed the partition model (PM), is based on two types of partition coefficients: octanol to water (Kow) and air to water (Kaw). The PM was able to effectively account for the variability in Kab data (n = 344), yielding an R2 value of 0.93 and root-mean-square error (RMSE) of 0.34 log unit. The predictive power and explanatory performance of the PM were found to be comparable to those of the parameter-intensive Abraham solvation models (ASMs). Additionally, the PM can be integrated into the software EPI Suite, which is widely used in chemical risk assessment for initial screening. The PM provides quick and reliable estimation of Kab compared to ASMs, while the GC×GC model is uniquely suited for estimating Kab values for complex mixtures of neutral organic compounds. In summary, our study introduces two novel and parsimonious models for the accurate estimation of Kab values for both individual compounds and complex mixtures.

The Solvation Shell of Small Solutes in Aqueous-Organic Solvent Mixtures and Its Implications for Reversed-Phase Liquid Chromatography

Reversed-phase liquid chromatography (RPLC) operates with water-organic solvent (W-OS) mobile phases where preferential solvation (PS) of solutes is likely. To investigate the relevance of the solute solvation shell in the mobile phase for RPLC retention, we combine data from molecular dynamics simulations of small, neutral solutes (six analytes and two dead time markers) in W-methanol (MeOH) and W-acetonitrile (ACN) mixtures with corresponding retention data obtained on an RPLC column over a wide range of W/OS ratios. Data derived from Kirkwood-Buff integrals show PS by the OS for analytes vs low or negative PS for dead time markers. W-ACN mixtures generate a higher amount of PS than W-MeOH mixtures, which contributes to the higher eluent strength of ACN in RPLC. Difference spatial distribution functions reveal anisotropic solvation shells with OS excess at hydrocarbon elements and W excess at functional groups, predicting that retention by the hydrophobic stationary phase is favored by hydrocarbon elements and limited by functional groups. Analysis of solute-solvent hydrogen bonds pinpoints the hydrogen-bond requirements toward W as the retention-limiting factor. The relation between the solute solvation shell and retention confirms the importance of W-OS and solute-W hydrogen bonding for RPLC retention.

Preparation of three structurally similar stationary phases with different ionizable terminal groups and evaluation of their retention performances under multiple modes in high performance liquid chromatography

Three structurally similar silane reagents with different terminal groups were prepared and bonded to silica to obtain three structurally similar stationary phases (Sil-Ph-COOH, Sil-Phe and Sil-Ph-NH2). The prepared stationary phases were characterized through elemental analysis (EA) and Fourier Transform Infrared Spectroscopy (FT-IR). These three stationary phases provided acceptable retention repeatability (relative standard deviations between 0.08% and 0.13%) and high column efficiency (7.3 × 104 plates/m for uridine on Sil-Phe). The retention behavior of the three columns was investigated under different chromatographic conditions including different mobile phase ratio, salt concentration, pH etc. The retention mechanisms were explored by linear solvation energy relationships and Van't Hoff plots. Applications in separation under reversed phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC) and ion exchange chromatography (IEC) mode were investigated. The results showed that the retention capacity of the stationary phases with different terminal groups to the analytes is very different, especially for carboxylic acids, because the surface charges of amino groups and carboxyl groups under weakly acidic conditions produce different electrostatic effects with dissociated carboxylic acids. Finally, the Sil-Phe column was employed to detect ibuprofen extracted from pharmaceutical ibuprofen capsules and vitamins extracted from vitamin tablets.

Characterization of solute-solvent interactions in liquid chromatography systems: A fast method based on Abraham's linear solvation energy relationships

The Abraham's solvation parameter model, based on linear solvation energy relationships (LSER), allows the accurate characterization of the selectivity of chromatographic systems according to solute-solvent interactions (polarizability, dipolarity, hydrogen bonding, and cavity formation). However, this method, based on multilinear regression analysis, requires the measurement of the retention factors of a considerably high number of compounds, turning it into a time-consuming low throughput method. Simpler methods such as Tanaka's scheme are preferred. In the present work, the Abraham's model is revisited to develop a fast and reliable method, similar to the one proposed by Tanaka, for the characterization of columns employed in reversed-phase liquid chromatography and particularly in hydrophilic interaction liquid chromatography. For this purpose, pairs of compounds are carefully selected in order to have in common all molecular descriptors except for a specific one (for instance, similar molecular volume, dipolarity, polarizability, and hydrogen bonding basicity features, but different hydrogen bonding acidity). Thus, the selectivity factor of a single pair of test compounds can provide information regarding the extent of the dissimilar solute-solvent interactions and their influence on chromatographic retention. The proposed characterization method includes the determination of the column hold-up volume and Abraham's cavity term by means of the injection of four alkyl ketone homologues. Therefore, five chromatographic runs in a reversed-phase column (four pairs of test solutes and a mixture of four homologues) are enough to characterize the selectivity of a chromatographic system. Tanaka's method is also analyzed from the LSER point of view.

The effect of the assigned descriptors for phthalate esters on the characterization of their separation properties using the solvation parameter model

Revised descriptors are determined for fifteen phthalate esters for use in the solvation parameter model and form part of the Wayne State University (WSU) compound descriptor database. For thirteen phthalate esters a comparison is made with the same compounds in the Abraham descriptor database. Gas chromatographic retention factors on poly(methyloctylsiloxane), SPB-Octyl, and poly(cyanopropylphenyldimethylsiloxane), DB-225, stationary phases are used to facilitate an assessment of the contribution of cavity formation and dispersion interactions, L descriptor, and dipole-type interactions, S descriptor, to the experimental retention factors (log k) for the phthalate esters with minimum interference from competing intermolecular interactions. The results indicate a systematic overprediction of the cavity and dispersion interaction term and underprediction of dipole-type interactions for the Abraham descriptors compared with the WSU descriptors for the phthalate esters. The average absolute deviation (AAD) for 13 phthalate esters on SPB-Octyl is 0.039 (WSU descriptors) compared with 0.252 (Abraham descriptors) and for 9 phthalate esters on DB-225 0.030 (WSU descriptors) compared with 0.167 (Abraham descriptors). The results for dipole-type interactions are confirmed and extended to include the hydrogen-bond basicity of the phthalate esters, B descriptor, by evaluation of partition constants in aqueous biphasic systems and the n-heptane-2,2,2-trifluoroethanol biphasic system. Differences in the contribution of the hydrogen-bond basicity of the phthalate esters to the experimental partition constants are largely random with respect to database selection but important for the accurate prediction of the partition constants. The AAD for the partition constant for 15 phthalate esters is 0.063 (WSU descriptors) compared with 0.320 (Abraham descriptors) for the heptane-2,2,2-trifluoroethanol biphasic system and 0.13 (WSU descriptors) compared with 0.25 (Abraham descriptors) for 9 phthalate esters in the octanol-water biphasic system. The WSU descriptors for the phthalate esters exhibit a better fit with the experimental data for separation systems and are free of the extreme values predicted for the Abraham descriptors for several phthalate esters.

The effect of descriptor database selection on the physicochemical characterization and prediction of water-air, octanol-air and octanol-water partition constants using the solvation parameter model

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.

Towards an accurate method for column void volume determination using liquid chromatography-mass spectrometry

Prediction of analyte retention times requires prior knowledge of the column void volume, the measurement of which is still highly contested within the literature and therefore experimental based prediction is often used. In this study, we investigated deuterated acetonitrile as an isotopically labelled mobile phase component to observe its elution behaviour in a binary mixture with water at 25 different mobile phase compositions (from 5 to 95 vol.% of acetonitrile), on two stationary phases (C8 and C18), and at two temperatures (30 and 40 °C) using LC-MS. The same experimental design was additionally used for three commonly used neutral void volume markers: uracil, phloroglucinol and N,N-dimethylformamide. Temperature was observed to influence the elution of acetonitrile in an inversely proportional manner with higher temperatures coinciding with lower elution times. By utilizing a three-way ANOVA, the composition of the mobile phase has been shown to have a significant effect on deuterated acetonitrile and other investigated void volume markers, demonstrating the fact that both void volume markers and acetonitrile itself exhibit retention-like behaviour. Excess adsorption isotherms for acetonitrile were calculated using deuterated acetonitrile elution data. The comparison of void volumes, obtained with conventional neutral void volume markers, revealed the former to be 24-36% lower than the void volume obtained using deuterated acetonitrile, as an isotopically labelled mobile phase component. For a water:acetonitrile mobile phase, the minor disturbance method using deuterated acetonitrile to obtain an integral average void volume (2.08 and 2.05 mL for C18 at 30 and 40 °C, respectively and 2.16 and 2.13 mL for C8 at 30 and 40 °C, respectively) was found to be the most appropriate method for determining the elusive column void volume.

An attempt to apply a subtraction model for characterization of non-polar stationary phase in supercritical fluid chromatography

This study verified the feasibility of using a subtraction model to characterize the non-polar stationary phases (including C4, C8, and phenyl-type) in supercritical fluid chromatography (SFC). The model with 6 terms was expressed as log α = η'H + θ'P + β'A + α'B + κ'C + σ'S, where a term θ'P indicating dipole or induced dipole interaction was intentionally supplemented. Ethylbenzene and SunFire C8 were respectively defined as the reference solute and column. A 7-step modeling procedure was proposed: in the first 6 steps, except σ'S, by the use of a bidirectional fitting method, other parameters were calculated based on the equation: log α = log (k_i/k_ref) ≈ η'H + θ'P + β'A + α'B + κ'C; and in the 7th step, residual analysis was employed to describe the σ'S term according to the equation: σ'S = log α_exp. - log α_pre. Furthermore, six columns that were not involved in modeling process and 12 compounds with unknown retention were used for methodology validation. It showed good predictions of log k, as demonstrated by adjusted determination coefficient (R²_adj) from 0.9927 to 0.9998 (column) and from 0.9940 to 0.9999 (compound), respectively. The subtraction model emphasized the contribution of dipole or induced dipole interaction to the retention in SFC, and it obtained the σ'S term through residual analysis. Moreover, it made reasonable physical-chemical sense as the linear solvation energy relationship (LSER) model did, with the distinct advantages of better fitting and more accurate prediction. This study provided some new insights into the characterization of non-polar stationary phases in SFC.

Recalibrating polyparameter linear free energy relationships and reanalyzing mechanisms for partition of nonionic organic compounds to low-density polyethylene passive sampler

Equilibrium passive sampling techniques based on the low-density polyethylene (LDPE) film are increasingly used for determining the concentration of contaminants in water and air. Reliable models capable of predicting LDPE-water and LDPE-air partition coefficients (K_iLDPEw and K_iLDPEa) would be very useful. In previous studies, polyparameter linear free energy relationships (PP-LFERs) based on Abraham's solute descriptors were calibrated for LDPE-water and LDPE-air systems. Unfortunately, a portion of unreliable partition coefficients and solute descriptors were included in the calibration sets of these previous studies, leading to unexpected system parameters and predictive performance in the regression results. In this study, more reliable PP-LFERs were recalibrated for LDPE-water and LDPE-air systems (20‒25 °C) using carefully collected reliable partition coefficients and solute descriptors of various polar and nonpolar compounds (over one hundred and with low redundancy) from the literature, as well as the robust regression method. The PP-LFERs performed well with root-mean-square errors of 0.15-0.25 log units and successfully predicted K_iLDPEw and K_iLDPEa values spanning over 10 orders of magnitude for compounds with reliable descriptors. The partitioning mechanisms of compounds to LDPE were also reanalyzed and compared in detail with n-alkanes (C₆-C₁₆). Generally, LDPE is more prone to form dispersion interactions with solutes than n-alkanes, while it is more difficult to form cavities in LDPE. In addition, the crystallinity of LDPE is not the sole reason for the distinct constant terms presenting in PP-LFERs for LDPE-water and n-hexadecane-water systems.

A machine learning based approach for estimating site-specific partition coefficient Kd of organic compounds: Application to nonionic pesticides

The partitioning coefficient K_d for a specific compound and location is not only a key input parameter of fate and transport models, but also critical in estimating the safety environmental concentration threshold. In order to reduce the uncertainty caused by non-linear interactions among environmental factors, machine learning based models for predicting K_d were developed in this work based on literature datasets of nonionic pesticides including molecular descriptors, soil properties, and experimental settings. The equilibrium concentration (C_e) values were specifically included for the reason that a varied range of K_d corresponding to a given C_e occurred in a real environment. By transforming 466 isotherms reported in the literature, 2618 paired equilibrium concentrations of liquid-solid (C_e-Q_e) data points were obtained. Results of SHapley Additive exPlanations revealed that soil organic carbon, C_e, and cavity formation were the most important. The distance-based applicability domain analysis was conducted for the 27 most frequently used pesticides with 15952 pieces of soil information from the HWSD-China dataset by setting three C_e scenarios (i.e., 10, 100, and 1000 μg L^-1). It was revealed the groups of compounds showing log K_d < 0.06 and log K_d > 1.19 were composed mostly of those with log K_ow of -0.800 and 5.50, respectively. When log K_d varied between 0.100 and 1.00, it was impacted by interactions among soil types, molecular descriptors, and C_e comprehensively, which accounted for 55% of the total 2618 calculations. It could be concluded that site-specific models developed in this work are necessary and practicable for the environmental risk assessment and management of nonionic organic compounds.

Selectivity evaluation of extraction systems

Extraction is the most common sample preparation technique prior to chromatographic analysis for samples which are too complex, too dilute, or contain matrix components incompatible with the further use of the separation system or interfere in the detection step. The most important extraction techniques are biphasic systems involving the transfer of target compounds from the sample to a different phase ideally accompanied by no more than a tolerable burden of co-extracted matrix compounds. The solvation parameter model affords a general framework to characterize biphasic extraction systems in terms of their relative capability for solute-phase intermolecular interactions (dispersion, dipole-type, hydrogen bonding) and within phase solvent-solvent interactions for cavity formation (cohesion). The approach is general and allows the comparison of liquid and solid extraction phases using the same terms and is used to explain the features important for the selective enrichment of target compounds by a specific extraction phase using solvent extraction, liquid-liquid extraction, and solid-phase extraction for samples in a gas, liquid, or solid phase. Hierarchical cluster analysis with the system constants of the solvation parameter model as variables facilitates the selection of solvents for extraction, the identification of liquid-liquid distribution systems with non-redundant selectivity, and evaluation of different approaches using liquids and solids for the isolation of target compounds from different matrices.

Correlating Pure Component Properties with MOSCED Solubility Parameters: Enthalpy of Vaporization and Vapor Pressure

Tools to predict vapor–liquid phase equilibria are indispensable for the conceptualization and design of separation processes. Modified separation of cohesive energy density (MOSCED) is a solubility-parameter-based method parameterized to make accurate predictions of the limiting activity coefficient. As a solubility-parameter-based method, MOSCED can not only make quantitative predictions, but can shed light on the underlying intermolecular interactions. In the present study, we demonstrated the ability of MOSCED to correlate the enthalpy of vaporization and vapor pressure at a specific temperature using multiple linear regression. With this addition, MOSCED is able to predict vapor–liquid phase equilibria in the absence of reference data. This was demonstrated for the prediction of the Henry’s constant and solvation free energy of organic solutes in water, which was found to be superior to mod-UNIFAC. In addition to being able to make phase equilibrium predictions, the ability to correlate the enthalpy of vaporization and vapor pressure offers the opportunity to include additional properties in the regression of the MOSCED parameters. Given this success, we additionally attempted to correlate a wide range of physical properties using a similar expression. While, in some cases, the results were reasonable, they were inferior to the correlations of the enthalpy of vaporization and vapor pressure. Future efforts will be needed to improve the correlations.

The influence of descriptor database selection on the solvation parameter model for separation processes

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 characterize the size (McGowan's characteristic volume), V, excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity and basicity, A and B, and the gas-liquid partition constant on n-hexadecane at 298.15 K, L. McGowan's characteristic volume and the excess molar refraction for liquids are available by calculation (E requires and experimental refractive index). The other descriptors and excess molar refraction for solids are experimental quantities and subject to greater variation or are estimated using computational or empirical models. Solute descriptors for several thousand compounds are available in the Abraham descriptor database and for several hundred compounds in the WSU descriptor database. These publicly accessible databases were developed independently using different approaches and for many compounds provide different descriptor values. In this report we evaluate the effect of mixing descriptors from the two databases on modeling chromatographic retention factors and liquid-liquid partition constants. It is shown that the two descriptor databases are not interchangeable. The WSU descriptor database consistently demonstrates improved model quality as determined by statistical parameters. Model system constants exhibit a general dependence on database selection with an approximately linear trend as a function of the fraction of compounds assigned descriptors from either database. There is no general model performance advantage to using mixed descriptor datasets and no real cause for concern for relatively large datasets containing < 15 % of compounds with descriptors assigned from the other database. For small datasets, descriptor quality is an important variable for adequate model performance.

APPLICATION OF MICELLAR LIQUID CHROMATOGRAPHY TO MODEL ECOTOXICITY OF PESTICIDES. COMPARISON WITH IMMOBILIZED ARTIFICIAL MEMBRANE CHROMATOGRAPHY AND N-OCTANOL-WATER PARTITIONING

The potential of Micellar Liquid Chromatography (MLC) to model ecotoxicological endpoints for a series of pesticides was investigated. To exploit the flexibility in MLC conditions, different surfactants were employed and retention mechanism was tracked and compared to Immobilized Artificial Membrane (IAM) chromatographic retention and n-octanol- water partitioning, logP. Neutral polyoxyethylene (23) lauryl ether (Brij-35), anionic sodium dodecyl sulfate (SDS) and cationic cetyltrimethylammonium bromide (CTAB) were used in presence of PBS at pH=7.40 and acetonitrile as organic modifier when necessary. Similarities/ dissimilarities between MLC retention and IAM or logP were investigated by Principal Component Analysis (PCA) and Liner Solvation Energy Relationships (LSER). LSER revealed that hydrogen bonding acidity is the most important factor for differentiation between MLC and IAM or logP. The impact of hydrogen bonding is exemplified in the relationships of MLC retention factors with IAM or logP, which necessitate the inclusion of a relevant descriptor. PCA further revealed that MLC retention factors are clustered together with IAM indices and logP within a broader ellipse formed by ecotoxicological endpoints, involving LC₅₀/ EC₅₀ values of six aquatic organisms namely Rainbow Trout, Fathead Minnow, Bluegill Sunfish, Sheepshead Minnow, Eastern Oyster and Water Flea as well as LD₅₀ values of Honey Bee, thus justifying their use to construct relevant models. Satisfactory specific models for individual organisms, as well as general fish models, were obtained, in most cases, upon combination of MLC retention factors with Molecular Weight (MW) or/ and hydrogen bond parameters. All models were evaluated and compared to previously reported IAM and logP based models using an external validation data set. Predictions with Brij-35 and SDS based models were comparable, although slightly inferior than those obtained with IAM, while they were in all cases better than those obtained with logP. CTAB led to a satisfactory prediction model for Honey Bee, but it was found less suitable for aquatic organisms.

An in-depth investigation of supercritical fluid chromatography retention mechanisms by evaluation of a series of specially designed alkylsiloxane-bonded stationary phases based on linear solvation energy relationship

Fundamental research on supercritical fluid chromatography (SFC) has gained considerable interest, with many studies focusing on its retention mechanism based on the linear solvation energy relationship (LSER) model. In this paper, a series of alkylsiloxane-bonded stationary phases were specifically designed and synthesized, then evaluated using the mobile phase composed of CO₂ with 10% (v/v) methanol. The study demonstrated the close relationship between the interactions (manner and magnitude) of stationary phases and the C-chain length, bonding density and the endcapping treatment. All C8 phases provide positive e, v and negative s, whose magnitude was regularly affected by bonding density. It was worth mentioning the non-endcapped C8 phases could provide H-bonding (positive a and b) by reducing the bonding density of the alkyl chain. Once it was endcapped, the interaction manner did not vary with bonding density adjustment. The non-endcapped C4 phases with higher bonding density could establish additional dispersion interaction (positive v). It can be seen that two synthesis strategies, 1) non-endcapped, long C-chain (C8) combined with low bonding density, and 2) non-endcapped, short C-chain (C4) combined with high bonding density, can obtain the alkylsiloxane-bonded stationary phases (C8-1 and C4-3) to provide both polar and dispersion interactions, showing different separation selectivity. Furthermore, the LSER model with ionic terms was applied to evaluate partial C8 columns, and its rationality was verified. The non-endcapped C8 showed great d⁺ values, which originated from the silanol groups. C8SCX also possessed a great d⁺ value due to the benzenesulfonic acid groups. A remarkable result showed that C8SAX exhibited prominent d^- and d⁺ values simultaneously due to the combined effect of silanol and quaternary ammonium groups, which indicates the unique selectivity when separating ionic compounds. This study provides in-depth insights into the retention mechanism of alkylsiloxane-bonded stationary phases in SFC, as well as a reference for the design of SFC stationary phases.

Evaluation of Hold-Up Volume Determination Methods and Markers in Hydrophilic Interaction Liquid Chromatography

Common methods for hold-up time and volume determination in Reversed-Phase Liquid Chromatography (RPLC) have been tested for Hydrophilic Interaction Liquid Chromatography (HILIC). A zwitterionic ZIC-HILIC column has been used for the testing. The pycnometric determination method, based on differences in column weight when filled with water or organic solvent, provides the overall volume of solvent inside the column. This includes the volume of eluent semi-sorbed on the packing of the column, which acts as the main stationary phase. The homologous series approach, based on the retention behavior of homologues in relation to their molecular volume, allows the determination of accurate hold-up volumes. However, the application of this method is time-consuming. In some cases, large neutral markers with poor dipolarity/polarizability and hydrogen bonding interactions can be used as hold-up volume markers. This is the case of dodecylbenzene and nonadecane-2-one in clearly HILIC behaving chromatographic systems, the use of decanophenone as a marker can be even extended to the boundary between HILIC and RPLC. The elution volume of the marker remains nearly unaffected by the concentration of ammonium acetate in the mobile phase up to 20 mM. The injection of pure solvents to produce minor base-line disturbance as hold-up markers is strongly discouraged, since solvent peaks are complex to interpret and depend on the ionic strength of the eluent.

Reliable prediction of sensory irritation threshold values of organic compounds using new models based on linear free energy relationships and GC×GC retention parameters

The human sensory irritation threshold (SIT) is an important biochemical parameter for the exposure assessment of organic air pollutants. First, we recalibrated the Abraham solvation models (ASMs) for 9 SIT endpoints by curating 720 individual experimental SIT values to find an accurate and parsimonious ASM variant, which exhibited root mean square error (RMSE) = 0.174-0.473 log unit. Second, we report linear free energy relationships - henceforth called partition models (PMs) - which exploit the correlations of 9 SIT endpoints with the linear combinations of partition coefficients for octanol-water and air-water systems showing RMSE = 0.221-0.591 log unit. These PMs can easily be integrated into widely used EPI-Suite™ screening tool. The explanatory and predictive performance of PMs were like parameter-intensive ASMs. Third, we present GC × GC models that are based on the retention times of the nonpolar analytes on the comprehensive two-dimensional gas chromatography (GC × GC), which successfully described the SIT variance (R²=0.959-0.996) and depicted a strong predictive power (RMSE = 0.359-0.660 log unit) for an independent set of nonpolar analytes. Taken together, PMs allow easy SIT screening of organic chemicals compared to ASMs. Unlike ASMs, our GC × GC models can be applied to estimate SIT of complex nonpolar mixtures.

Preparation of three regioisomeric ionic liquid stationary phases and investigation of their retention behavior

The structural properties of ionic liquid stationary phases have a considerable effect on their separation selectivity. However, the difference of the chromatographic retention behavior of different regioisomeric ionic liquid stationary phases has rarely been investigated. In this study, three regioisomeric ionic liquid silane reagents were prepared by photoinitiated ene-click chemistry and bonded to silica by one-pot method to fabricate three new stationary phases (Sil-C2Im-C8, Sil-C6Im-C4, and Sil-C9Im-C1). All three stationary phases showed promising retention repeatability and efficiency. The retention behavior of the three stationary phases was investigated under various chromatographic conditions. The retention mechanism was further investigated by the linear energy solvation relationship and Van't Hoff plots. The stationary phases exhibited mixed-mode retention mechanisms. The π-π, hydrogen bonding, ion-exchange, and hydrophilic interactions with analytes were the weakest when the imidazole ions were embedded in the innermost part of the alkyl chains, while the interactions were the strongest when the imidazole ions were embedded in the middle of the alkyl chains. The three stationary phases provided great but different separation performances towards nucleosides, nucleobases, aromatic acids, alkyl benzenes, and polycyclic aromatic hydrocarbons due to the influence of imidazole ion position.

Recent advances for estimating environmental properties for small molecules from chromatographic measurements and the solvation parameter model

The transfer of neutral compounds between immiscible phases in chromatographic or environmental systems can be described by six solute properties (solute descriptors) using the solvation parameter model. The solute descriptors are size (McGowan's characteristic volume), V, excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity and basicity, A and B, and the gas-liquid partition constant on n-hexadecane at 298.15 K, L. V and E for liquids are accessible by calculation but the other descriptors and E for solids are determined experimentally by chromatographic, liquid-liquid partition, and solubility measurements. These solute descriptors are available for several thousand compounds in the Abraham solute descriptor databases and for several hundred compounds in the WSU experimental solute descriptor database. In the first part of this review, we highlight features important in defining each descriptor, their experimental determination, compare descriptor quality for the two organized descriptor databases, and methods for estimating Abraham solute descriptors. In the second part we focus on recent applications of the solvation parameter model to characterize environmental systems and its use for the identification of surrogate chromatographic models for estimating environmental properties.

Separation of phosphorothioate oligonucleotide impurities by WAX HPLC under high organic content elution conditions

The separation of impurities in phosphorothioate diester (PS) oligonucleotides is complicated by (1) the presence of a very large number of diastereoisomers, e.g., 2¹⁹ for a 20-mer oligonucleotide, (2) peak broadening due to the hydrophobic character of the sulfur atom, and (3) the chemical similarity of the impurities to the parent oligonucleotide and each other. Further difficulties arise due to the chemical nature of oligonucleotides, which display a complex mixture of ionic, hydrophobic, H-bonding, and other functionalities. To minimize hydrophobic interactions and peak broadening due to the PS modification, we have developed a novel method that combines a weak anion exchange (WAX) column with a mobile phase elution system designed to maximize separation by a single ionic/electrostatic interaction. We found that although chaotropes are helpful, the most significant beneficial effect of the hydrophilic WAX column is that high-organic, low-salt mobile phase is required for product elution. Separations are also benefitted by pH gradient effects on stationary phase electrostatic potential and analyte ionization. An extraordinary degree of separation is achieved by the new WAX method in comparison to SAX (strong anion exchange) chromatography. For the first time, the extent of deamination of PS oligonucleotides is directly determined by a chromatography-only method. The approach, representative results, and the mechanisms of separation are discussed.

Exploring the role of octanol-water partition coefficient and Henry's law constant in predicting the lipid-water partition coefficients of organic chemicals

Partition coefficients for storage lipid-water (logKlw) and phospholipid-water (logKpw) 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 logKlw, and of logKpw with the linear combinations of the octanol-water partition coefficient (logKow) and the dimensionless Henry's law constant (air-water partition coefficient, logKaw). The calibrated partition models successfully describe the variations in logKlw data (n = 305, R2 = 0.971, root-mean-square-error (rmse) = 0.375), and in logKpw data (n = 131, R2 = 0.953, rmse = 0.413). With the inputs of logKow and logKaw estimated from the U.S. EPA's EPI Suite, our models of logKlw and logKpw 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 logKlw and logKpw in terms of hydrophobicity and volatility trait of chemicals.

Application of machine learning to predict the inhibitory activity of organic chemicals on thyroid stimulating hormone receptor

With the promotion of carbon neutrality, it is also important to synchronously promote the assessment and sustainable management of chemicals so as to protect public health. Humans and animals are possibly exposed to endocrine disruptors that have inhibitory effects on thyroid stimulating hormone receptor (TSHR). As such, it is important to identify chemicals that inhibit TSHR and to develop models to predict their inhibitory activity. In this study, 5952 compounds derived from a cyclic adenosine monophosphate (cAMP) analysis, a key signaling pathway in thyrocytes, were used to establish a binary classification model comparing methods that included random forest (RF), extreme gradient boosting (XGB), and logistic regression (LR). The prediction model based on RF showed the highest identification accuracy for revealing chemicals that may inhibit TSHR. For the RF model, recall was calculated at 0.89, balance accuracy was 0.85, and its receiver operating characteristic (ROC) curve-area under (AUC) was 0.92, indicating that the model had very high predictive capacity. The lowest CDocker energy (CE) and CDocker interaction energy (CIE) for chemicals and TSHR were determined and were subsequently introduced into the predictive model as descriptors. A regression model, extreme gradient boosting-Regression (XGBR), was successfully established yielding an R² = 0.65 to predict inhibitory activity for active compounds. Parameters that included dissociation characteristics, molecular structure, and binding energy were all key factors in the predictive model. We demonstrate that QSAR models are useful approaches, not only for identifying chemicals that inhibit TSHR, but for predicting inhibitory activity of active compounds.

Acoustic Wave Sensors for Detection of Blister Chemical Warfare Agents and Their Simulants

On-site detection and initial identification of chemical warfare agents (CWAs) remain difficult despite the many available devices designed for this type of analysis. Devices using well-established analytical techniques such as ion mobility spectrometry, gas chromatography coupled with mass spectrometry, or flame photometry, in addition to unquestionable advantages, also have some limitations (complexity, high unit cost, lack of selectivity). One of the emerging techniques of CWA detection is based on acoustic wave sensors, among which surface acoustic wave (SAW) devices and quartz crystal microbalances (QCM) are of particular importance. These devices allow for the construction of undemanding and affordable gas sensors whose selectivity, sensitivity, and other metrological parameters can be tailored by application of particular coating material. This review article presents the current state of knowledge and achievements in the field of SAW and QCM-based gas sensors used for the detection of blister agents as well as simulants of these substances. The scope of the review covers the detection of blister agents and their simulants only, as in the available literature no similar paper was found, in contrast to the detection of nerve agents. The article includes description of the principles of operation of acoustic wave sensors, a critical review of individual studies and solutions, and discusses development prospects of this analytical technique in the field of blister agent detection.

A story of peptides, lipophilicity and chromatography - back and forth in time

Peptides, as part of the beyond the rule of 5 (bRo5) chemical space, represent a unique class of pharmaceutical compounds. Because of their exceptional position in the chemical space between traditional small molecules (molecular weight (MW) < 500 Da) and large therapeutic proteins (MW > 5000 Da), peptides became promising candidates for targeting challenging binding sites, including even targets traditionally considered as undruggable - e.g. intracellular protein-protein interactions. However, basic knowledge about physicochemical properties that are important for a drug to be membrane permeable is missing but would enhance the drug discovery process of bRo5 molecules. Consequently, there is a demand for quick and simple lipophilicity determination methods for peptides. In comparison to the traditional lipophilicity determination methods via shake flask and in silico prediction, chromatography-based methods could have multiple benefits such as the requirement of low analyte amount, insensitivity to impurities and high throughput. Herein we elucidate the role of peptide lipophilicity and different lipophilicity values. Further, we summarize peptide analysis via common chromatographic techniques, in specific reversed phase liquid chromatography, hydrophilic interaction liquid chromatography and supercritical fluid chromatography and their role in drug discovery and development process.

An Assessment of Stationary Phase Selectivity in SFC

Supercritical fluid chromatography (SFC) has seen a recent resurgence in interest following investment in the development of instrument technology by numerous instrument manufacturers. Increased focus on sustainability in chromatographic science, coupled with the orthogonality to reversed phase HPLC, is likely to further drive the uptake of SFC in many sectors. As with any form of chromatography, optimizing separation selectivity is a key variable in providing adequate resolution and accurate identification and quantification of target analytes. Stationary phase chemistry can be readily exploited to substantially alter the separation selectivity obtained. This article examines and characterizes the selectivity differences offered by three prototype SFC phases.

Inverse gas chromatography as a tool for screening materials: The relation between Lewis acid-base constants and triboelectric charge density of polymers

Since Saint-Flour and Papirer first introduced Gutmann's acceptor number and donor number parameters into the inverse gas chromatography (IGC) field in 1982, IGC has become an important technology for the measurement of surface Lewis acid-base properties of solid materials. However, introducing new roles of Lewis acid-base parameters, especially using them to predict material properties rather than just explain material properties, is an important aspect in developing IGC technology. In this paper, we first introduce the Schultz and Abraham methods for measurement of acid-base properties and discuss the traditional role of acid-base parameters. Then, we present a relation between the ratio of acid-base constants, K_a/K_b, and triboelectric charge density of some polymers to prove the possible new application field of IGC.

Solute–Solvent Interactions in Hydrophilic Interaction Liquid Chromatography: Characterization of the Retention in a Silica Column by the Abraham Linear Free Energy Relationship Model

The Abraham linear free energy relationship model has been used to characterize a hydrophilic interaction liquid chromatography (HILIC) silica column with acetonitrile/water and methanol/water mobile phases. Analysis by the model for acetonitrile/water mobile phases points to solute volume and hydrogen bond basicity as the main properties affecting retention, whereas solute hydrogen bond acidity, dipolarity and polarizability practically do not affect it. Formation of a cavity is easier in acetonitrile-rich mobile phases than in the aqueous stationary phase, and hence increase of solute volume decreases retention. Conversely, hydrogen bond acidity is stronger in the aqueous stationary phase than in the acetonitrile-rich mobile phase and thus an increase of solute hydrogen bond basicity increases retention. Results are similar for methanol/water mobile phases with the difference that solute hydrogen bond acidity is significant too. Increase in hydrogen bond acidity of the solute decreases retention showing that methanol mobile phases must be better hydrogen bond acceptors than acetonitrile ones, and even than water-rich stationary phases. The results are like the ones obtained in zwitterionic HILIC columns bonded to silica or polymer supports for acetonitrile/water mobile phases, but different for solute hydrogen bond acidity for a polymer bonded zwitterionic column with methanol/water mobile phases, indicating that bonding support plays an important role in HILIC retention. Comparison to RPLC characterized systems confirms the complementarity of HILIC systems to RPLC ones because the main properties affecting retention are the same but with reversed coefficients. The least retained solutes in RPLC are the most retained in HILIC.

Linear Solvation Energy Relationships (LSERs) for Robust Prediction of Partition Coefficients between Low Density Polyethylene and Water Part I: Experimental Partition Coefficients and Model Calibration

When equilibrium of leaching is reached within a product's duty cycle, partition coefficients polymer/solution dictate the maximum accumulation of a leachable and thus, patient exposure by leachables. Yet, in the pharmaceutical and food industry, exposure estimates based on predictive modeling typically rely on coarse estimations of the partition coefficient, with accurate and robust models lacking. This first part of the study aimed to explore linear solvation energy relationships (LSERs) as high performing models for the prediction of partition coefficients polymer/water. For this, partition coefficients between low density polyethylene (LDPE) and aqueous buffers for 159 compounds spanning a wide range of chemical diversity, molecular weight, vapor pressure, aqueous solubility and polarity (hydrophobicity) were determined and complimentary data collected from the literature (n=159, MW: 32 to 722, logK_i,O/W: -0.72 to 8.61 and logK_i,LDPE/W: -3.35 up to 8.36). The chemical space represented by this compounds set is considered indicative for the universe of compounds potentially leaching from plastics. Based on the dataset for the LDPE material purified by solvent extraction, a LSER model for partitioning between LDPE and water was calibrated to give:logK_i,LDPE/W=-0.529+1.098E_i-1.557S_i-2.991A_i-4.617B_i+3.886V_i. The model was proven accurate and precise (n = 156, R² = 0.991, RMSE = 0.264). Further, it was demonstrated superior over a log-linear model fitted to the same data. Nonetheless, it could be shown that log-linear correlations against logK_i,O/W can be of value for the estimation of partition coefficients for nonpolar compounds exhibiting low hydrogen-bonding donor and/or acceptor propensity. For these nonpolar compounds, the log - linear model was found to be: logK_i,LDPE/W=1.18logK_i,O/W-1.33 (n = 115, R²=0.985, RMSE = 0.313). In contrast, with mono-/bipolar compounds included into the regression data set, an only weak correlation was observed (n = 156, R² = 0.930, RMSE = 0.742) rendering the log-linear model of more limited value for polar compounds. Notably, sorption of polar compounds into native (non-purified) LDPE was found to be up to 0.3 log units lower than into purified LDPE. To identify maximum (i. e. worst-case) levels of leaching in support of chemical safety risk assessments on systems attaining equilibrium before end of shelf-life, it appears adequate to utilize LSER - calculated partition coefficients (in combination with solubility data) by ignoring any kinetical information.

Combinatorial selectivity with an array of phthalocyanines functionalized TiO2/ZnO heterojunction thin film sensors

The development of electronic noses requires the control of the selectivity pattern of each sensor of the array. Organic chemistry offers a manifold of possibilities to this regard but in many cases the chemical sensitivity is not matched with the response of electronic sensor. The combination of organic and inorganic materials is an approach to transfer the chemical sensitivities of the sensor to the measurable electronic signals. In this paper, this approach is demonstrated with a hybrid material made of phthalocyanines and a bilayer structure of ZnO and TiO₂. Results show that the whole spectrum of sensitivity of phthalocyanines results in changes of the resistance of the sensor, and even the adsorption of compounds, such as hexane, which cannot change the resistance of pure phthalocyanine layers, elicits changes of the sensor resistance. Furthermore, since phthalocyanines are optically active, the sensitivity in dark and visible light are different. Thus, operating the sensor in dark and light two different signals per sensors can be extracted. As a consequence, an array of 3 sensors made of different phthalocyanines results in a virtual array of six sensors. The sensor array shows a remarkable selectivity respect to a set of test compounds. Principal component analysis scores plot illustrates that hydrogen bond basicity and dispersion interaction are the dominant mechanisms of interaction.

Volume and composition of semi-adsorbed stationary phases in hydrophilic interaction liquid chromatography. Comparison of water adsorption in common stationary phases and eluents

Pycnometric and homologous series retention methods are used to determine the volume and mean composition of the water-rich layers partially adsorbed on the surface of several hydrophilic interaction liquid chromatography (HILIC) column fillings with acetonitrile-water and methanol-water as eluents. The findings obtained in this work confirm earlier studies using direct methods for measuring the stationary phase water content performed by Jandera's and Irgum's research groups. Water is preferentially adsorbed on the surface of the HILIC bonded phase in hydroorganic eluents containing more than 40% acetonitrile or 70% methanol, and a gradient of several water-rich transition layers between the polar bonded phase and the poorly polar bulk mobile phase is formed. These layers of reduced mobility act as HILIC stationary phases, retaining polar solutes. The volume of these layers and concentration of adsorbed water is much larger for acetonitrile-water than for methanol-water mobile phases. In hydroorganic eluents with less than 20-30% acetonitrile or 40% methanol the amount of preferentially adsorbed water is very small, and the observed retention behavior is close to the one in reversed-phase liquid chromatography (RPLC). In eluents with intermediate acetonitrile-water or methanol-water compositions a mixed HILIC-RPLC behavior is presented. Comparison of several HILIC columns shows that the highest water enrichment in the HILIC retention region for acetonitrile-water mobile phases is observed for zwitterionic and aminopropyl bonded phases, followed in minor grade for diol and polyvinyl alcohol functionalizations. Pentafluorophenyl bonded phase, usually considered a HILIC column, does not show significant water adsorption, nor HILIC retention.

Inverse gas chromatographic evaluation of polysiloxanes containing phenolic and fluorophenolic functional groups for use in gas sensors

The paper presents the results of inverse gas chromatographic (IGC) research on two novel polysiloxanes: poly{dimethylsiloxane-co -[4-(2,3-difluoro-4-hydroxyphenoxy)butyl]methylsiloxane} and poly{dimethylsiloxane-co -[4-(4-hydroxyphenoxy)butyl]methylsiloxane}, dubbed PMFOS and PMOS respectively, designed for use as chemosensitive coatings for acoustoelectronic sensors. These materials contain phenolic functional substituents that differ by the presence of fluorine atoms. The materials' solvation properties were identified by IGC with application of an LSER solvation model at temperatures ranging from 40 to 120 °C. In the case of both polysiloxanes, the research revealed that the dominant type of intermolecular interaction was the formation of acidic hydrogen bonds. The material with fluorine-activated hydroxyl groups, PMFOS, is much more acidic and less basic than the other one and thus more interesting. According to LSER, PMFOS exhibits high affinity and selectivity to hydrogen bond bases. In addition, the material retains its properties even at a temperature of 120 °C.

Kinetic Modeling of API Oxidation: (1) The AIBN/H2O/CH3OH Radical "Soup"

Stress testing of active pharmaceutical ingredients (API) is an important tool used to gauge chemical stability and identify potential degradation products. While different flavors of API stress testing systems have been used in experimental investigations for decades, the detailed kinetics of such systems as well as the chemical composition of prominent reactive species, specifically reactive oxygen species, are unknown. As a first step toward understanding and modeling API oxidation in stress testing, we investigated a typical radical "soup" solution an API is subject to during stress testing. Here we applied ab initio electronic structure calculations to automatically generate and refine a detailed chemical kinetics model, taking a fresh look at API oxidation. We generated a detailed kinetic model for a representative azobis(isobutyronitrile) (AIBN)/H₂O/CH₃OH stress-testing system with a varied cosolvent ratio (50%/50%-99.5%/0.5% vol water/methanol) for 5.0 mM AIBN and representative pH values of 4-10 at 40 °C that was stirred and open to the atmosphere. At acidic conditions, hydroxymethyl alkoxyl is the dominant alkoxyl radical, and at basic conditions, for most studied initial methanol concentrations, cyanoisopropyl alkoxyl becomes the dominant alkoxyl radical, albeit at an overall lower concentration. At acidic conditions, the levels of cyanoisopropyl peroxyl, hydroxymethyl peroxyl, and hydroperoxyl radicals are relatively high and comparable, while, at both neutral and basic pH conditions, superoxide becomes the prominent radical in the system. The present work reveals the prominent species in a common model API stress testing system at various cosolvent and pH conditions, sets the stage for an in-depth quantitative API kinetic study, and demonstrates the usage of novel software tools for automated chemical kinetic model generation and ab initio refinement.