Chromatographic Retention Research Articles

Study on binding affinity profile, bioactivity, and lipophilicity of selected antipsychotic drugs

Schizophrenia is a complex mental illness that affects almost 1% of the population and has no curative treatment. Currently, available neuroleptic drugs have severe limitations and induce drug-related adverse effects. Receptor binding affinity parameters and lipophilicity are important characteristics that describe the bioactivity of these drugs. Lipophilicity is an important physicochemical property of a drug, which predicts distribution, binding to plasma protein, crossing the blood–brain barrier, and biological activity. Five antipsychotic drugs (Haloperidol, Risperidone, Aripiprazole, Olanzapine, and Quetiapine) were selected and the experimental determination of lipophilicity was carried out by reverse phase thin-layer chromatography (RP-TLC) using four types of stationary phases (RP-18, CN, Diol, and NH2 modified silica gel HPTLC plates) and acetonitrile-water with increasing percentage of acetonitrile and 0.2% formic acid in each case as mobile phase. Lipophilicity parameters (mRM and RM0) calculated from the experimental chromatographic retention data were discussed in terms of the correlation with different receptor binding affinity parameters determined by computational methods.

The flavagline FL3 interferes with the association of Annexin A2 with the eIF4F initiation complex and transiently stimulates the translation of annexin A2 mRNA.

Introduction: Annexin A2 (AnxA2) plays a critical role in cell transformation, immune response, and resistance to cancer therapy. Besides functioning as a calcium- and lipidbinding protein, AnxA2 also acts as an mRNA-binding protein, for instance, by interacting with regulatory regions of specific cytoskeleton-associated mRNAs. Methods and Results: Nanomolar concentrations of FL3, an inhibitor of the translation factor eIF4A, transiently increases the expression of AnxA2 in PC12 cells and stimulates shortterm transcription/translation of anxA2 mRNA in the rabbit reticulocyte lysate. AnxA2 regulates the translation of its cognate mRNA by a feed-back mechanism, which can partly be relieved by FL3. Results obtained using the holdup chromatographic retention assay results suggest that AnxA2 interacts transiently with eIF4E (possibly eIF4G) and PABP in an RNA-independent manner while cap pulldown experiments indicate a more stable RNA-dependent interaction. Short-term (2 h) treatment of PC12 cells with FL3 increases the amount of eIF4A in cap pulldown complexes of total lysates, but not of the cytoskeletal fraction. AnxA2 is only present in cap analogue-purified initiation complexes from the cytoskeletal fraction and not total lysates confirming that AnxA2 binds to a specific subpopulation of mRNAs. Discussion: Thus, AnxA2 interacts with PABP1 and subunits of the initiation complex eIF4F, explaining its inhibitory effect on translation by preventing the formation of the full eIF4F complex. This interaction appears to be modulated by FL3. These novel findings shed light on the regulation of translation by AnxA2 and contribute to a better understanding of the mechanism of action of eIF4A inhibitors.

Comprehensive characterization of narirutin metabolites in vitro and in vivo based on Analogous-Core recursion analysis strategy using UHPLC-Q-Exactive Orbitrap MS/MS

Narirutin, extracted from the dried ripe pericarp of Rutaceae orange and its cultivated varieties, is a dihydroflavone compound with various biological activities and pharmacological effects. So far as we know, the metabolism profiling of narirutin has been insufficient until now. In the present study, an efficient method was employed to perform rapid analysis and identification of narirutin metabolites by using ultra-high performance liquid chromatography quadrupole exactive orbitrap MS/MS (UHPLC-Q-Exactive Orbitrap MS/MS) combined with an analogous core recursion (ACR) analysis strategy. Firstly, according to the basic core structure of the dihydroflavonoid, the cleavage mode and fragmentation ions of narirutin were summarized. Secondly, based on the difference of the substituent groups, the fragment ions of narirutin were preliminarily inferred and verified by the secondary mass spectra of its standard compound. Thirdly, the fragment ions of narirutin in positive and negative ion modes were summarized to provide a basis for the identification of metabolites. Fourthly, candidate metabolites were accurately and tentatively identified according to the cleavage law of mass spectrometry, literature reports, comparison of reference substances, and especially the diagnostic fragment ion clusters (DFICs) and characteristic suggestive ions (CSIs) deduced preliminarily. Finally, a total of 46 metabolites (30 in vivo and 19 in vitro), including prototype drugs were identified based on the ACR analysis strategy, chromatographic retention behavior of metabolites, corresponding ClogP value and accurate molecular weight. Among them, 22 metabolites were discovered in rats plasma, 12 in urine, 4 in liver tissue, 19 in liver microsomes, respectively. Additionally, metabolites relative contents were also studied by extracted ion chromatography (EIC) method. Our result also illustrated that narirutin primarily underwent glucuronidation, sulfation, glutathione binding, deglycosylation, oxidation, reduction, methylation, hydroxylation, ring-opening and their composite reactions. A novel strategy was constructed to comprehensively elucidate the biotransformation pathways of narirutin in vitro and in vivo, and a systematic metabolic profile of narirutin was generated. This study provided a great reference for further understanding of the biotransformation pathways and guiding for clinical application of narirutin.

Diazo probe-based chemical isotope labeling assisted liquid chromatography-tandem mass spectrometry analysis for sensitive determination of amino acids in biofluids

Amino acids are important biomolecules and contribute to essential biological processes. Liquid chromatography tandem mass spectrometry (LC–MS) now is a powerful tool for the analysis of amino acid metabolites; however, the structural similarity and polarity of amino acids can lead to the poor chromatographic retention and low detection sensitivities. In this study, we used a pair of light and heavy isotopomers of diazo probes, d0/d5-2-(diazomethyl)-N-methyl-N-phenyl-benzamide (2-DMBA/d5 -2-DMBA) to label amino acids. The paired MS probes of 2-DMBA and d5 -2-DMBA carry diazo groups that can efficiently and specifically react with the carboxyl group on free amino acid metabolites under mild conditions. Benefiting from the transfer of the 2-DMBA/d5 -2-DMBA to carboxyl group on amino acids, the ionization efficiencies of amino acids presented great enhancement during LC–MS analysis. The results suggested that the detection sensitivities of 17 amino acids increased by 9-133-fold upon 2-DMBA labeling, and the obtained limits of detection (LODs) of amino acids on-column ranged from 0.011 fmol-0.057 fmol. With the application of the developed method, we successfully achieved the sensitive and accurate detection of the 17 amino acids in microliter level of serum sample. Moreover, the contents of most amino acids were different in the serum from normal and B16F10-tumour mice, demonstrating that endogenous amino acids may play important roles in the regulation of tumors development. This developed method of chemical labeling of amino acids with diazo probes assisted LC–MS analysis provides a potentially valuable tool to investigate the relationships between amino acids metabolism and diseases.

Simultaneous effect of different chromatographic conditions on the chromatographic retention of pentapeptide derivatives (HGRFG and NPNPT).

Introduction: Oligopeptides exhibit great prospects for clinical application and its separation is of great importance in new drug development. Methods: To accurately predict the retention of pentapeptides with analogous structures in chromatography, the retention times of 57 pentapeptide derivatives in seven buffers at three temperatures and four mobile phase compositions were measured via reversed-phase high-performance liquid chromatography. The parameters ( , , and ) of the acid-base equilibrium were obtained by fitting the data corresponding to a sigmoidal function. We then studied the dependence of these parameters on the temperature (T), organic modifier composition (φ, methanol volume fraction), and polarity ( parameter). Finally, we proposed two six-parameter models with (1) pH and T and (2) pH and φ or as the independent variables. These models were validated for their prediction capacities by linearly fitting the predicted retention factor k-value and the experimental k-value. Results: The results showed that and exhibited linear relationships with , φ or for all pentapeptides, especially for the acid pentapeptides. In the model of pH and T, the correlation coefficient (R2) of the acid pentapeptides was 0.8603, suggesting a certain prediction capability of chromatographic retention. Moreover, in the model of pH and φ or , the R2 values of the acid and neutral pentapeptides were greater than 0.93, and the average root mean squared error was approximately 0.3, indicating that the k-values could be effectively predicted. Discussion: In summary, the two six-parameter models were appropriate to characterize the chromatographic retention of amphoteric compounds, especially the acid or neutral pentapeptides, and could predict the chromatographic retention of pentapeptide compounds.

Improved Chromatography and MS-Based Detection of Glyphosate and Aminomethylphosphonic Acid Using iTrEnDi.

Glyphosate (GLY), a synthetic, nonselective systemic herbicide that is particularly effective against perennial weeds, is the most used weedkiller in the world. There are growing concerns over GLY accumulation in the environment and the attendant human health-associated risks, and despite increased attention in the media, GLY and its breakdown product aminomethylphosphonic acid (AMPA) remain elusive to many analytical strategies. Chemical derivatization coupled with high-performance liquid chromatography-mass spectrometry (HPLC-MS) addresses the challenge of quantifying low levels of GLY and AMPA in complex samples. Here we demonstrate the use of in situ trimethylation enhancement using diazomethane (iTrEnDi) to derivatize GLY and AMPA into permethylated products ([GLYTr]+ and [AMPATr]+, respectively) prior to analysis via HPLC-MS. iTrEnDi produced quantitative yields and resulted in a 12-340-fold increases in HPLC-MS-based sensitivity for [GLYTr]+ and [AMPATr]+, respectively, compared with underivatized counterparts. The limits of detection of derivatized compounds were found to be 0.99 ng/L for [GLYTr]+ and 1.30 ng/L for [AMPATr]+, demonstrating significant sensitivity improvements compared to previously established derivatization techniques. iTrEnDi is compatible with the direct derivatization of Roundup formulations. Finally, as proof of principle, a simple aqueous extraction followed by iTrEnDi enabled the detection of [GLYTr]+ and [AMPATr]+ on the exterior of field-grown soybeans that were sprayed with Roundup. Overall, iTrEnDi ameliorates issues relating to low proton affinity and chromatographic retention, boosting HPLC-MS-based sensitivity and enabling the elucidation of elusive analytes such as GLY and AMPA within agricultural systems.

Intelligent Workflow and Software for Non-Target Analysis of Complex Samples Using a Mixture of Toxic Transformation Products of Unsymmetrical Dimethylhydrazine as an Example.

Unsymmetrical dimethylhydrazine (UDMH) is a widely used rocket propellant. Entering the environment or being stored in uncontrolled conditions, UDMH easily forms an enormous variety (at least many dozens) of transformation products. Environmental pollution by UDMH and its transformation products is a major problem in many countries and across the Arctic region. Unfortunately, previous works often use only electron ionization mass spectrometry with a library search, or they consider only the molecular formula to propose the structures of new products. This is quite an unreliable approach. It was demonstrated that a newly proposed artificial intelligence-based workflow allows for the proposal of structures of UDMH transformation products with a greater degree of certainty. The presented free and open-source software with a convenient graphical user interface facilitates the non-target analysis of industrial samples. It has bundled machine learning models for the prediction of retention indices and mass spectra. A critical analysis of whether a combination of several methods of chromatography and mass spectrometry allows us to elucidate the structure of an unknown UDMH transformation product was provided. It was demonstrated that the use of gas chromatographic retention indices for two stationary phases (polar and non-polar) allows for the rejection of false candidates in many cases when only one retention index is not enough. The structures of five previously unknown UDMH transformation products were proposed, and four previously proposed structures were refined.

Immobilized Keratin HPLC Stationary Phase-A Forgotten Model of Transdermal Absorption: To What Molecular and Biological Properties Is It Relevant?

Chromatographic retention data collected on immobilized keratin (KER) or immobilized artificial membrane (IAM) stationary phases were used to predict skin permeability coefficient (log Kp) and bioconcentration factor (log BCF) of structurally unrelated compounds. Models of both properties contained, apart from chromatographic descriptors, calculated physico-chemical parameters. The log Kp model, containing keratin-based retention factor, has slightly better statistical parameters and is in a better agreement with experimental log Kp data than the model derived from IAM chromatography; both models are applicable primarily to non-ionized compounds.Based on the multiple linear regression (MLR) analyses conducted in this study, it was concluded that immobilized keratin chromatographic support is a moderately useful tool for skin permeability assessment.However, chromatography on immobilized keratin may also be of use for a different purpose-in studies of compounds' bioconcentration in aquatic organisms.

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.

Using Machine Learning To Predict Partition Coefficient (Log P) and Distribution Coefficient (Log D) with Molecular Descriptors and Liquid Chromatography Retention Time.

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 R2 = 0.89), and Shapley additive explanations analysis indicates that RT has the highest impact on model accuracy.

Per- and Polyfluoroalkyl Substances Enrichment in the Surface Microlayer of a Freshwater System Impacted by Aqueous Film-Forming Foams

Accumulation of per- and polyfluoroalkyl substances (PFAS) in the surface microlayer (SML) of open water bodies has received little attention. Various SML sampling methods exist, yet none have been systematically evaluated for PFAS. Three glass-based techniques were deployed for SML sampling at 10 sites on a freshwater system impacted by aqueous film-forming foam (AFFF). Samples of SML and underlying bulk water (3 and 30 cm) were analyzed for 50 target PFAS by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF). Single dipped microscope slides yielded field measurements of SML thicknesses and enrichment factors for eight PFAS and used to compute field-measured air–water adsorption coefficients. Large glass plates collected a greater volume of SML, gave lower variability, and lower limits of detection and quantification. Up to 19 PFAS (concentrations up to 13,000 ng/L) were associated with the SML, while only 15 PFAS were in underlying bulk water. Enrichment factors (EFs) ranged from 1 to 20 and increased with chromatographic retention time, a proxy for relative hydrophobicity. Field-measured air–water adsorption coefficients were consistent with monolayer adsorption as described by the Gibbs adsorption equation, which indicates that only adsorption to the air–water interface is needed to explain the observed PFAS enrichment in the SML.

Profiling of cool-season forage arabinoxylans via a validated HPAEC-PAD method.

Cool-season pasture grasses contain arabinoxylans (AX) as their major cell wall hemicellulosic polysaccharide. AX structural differences may influence enzymatic degradability, but this relationship has not been fully explored in the AX from the vegetative tissues of cool-season forages, primarily because only limited AX structural characterization has been performed in pasture grasses. Structural profiling of forage AX is a necessary foundation for future work assessing enzymatic degradability and may also be useful for assessing forage quality and suitability for ruminant feed. The main objective of this study was to optimize and validate a high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) method for the simultaneous quantification of 10 endoxylanase-released xylooligosaccharides (XOS) and arabinoxylan oligosaccharides (AXOS) in cool-season forage cell wall material. The following analytical parameters were determined or optimized: chromatographic separation and retention time (RT), internal standard suitability, working concentration range (CR), limit of detection (LOD), limit of quantification (LOQ), relative response factor (RRF), and quadratic calibration curves. The developed method was used to profile the AX structure of four cool-season grasses commonly grown in pastures (timothy, Phleum pratense L.; perennial ryegrass, Lolium perenne L.; tall fescue, Schedonorus arundinaceus (Schreb.) Dumort.; and Kentucky bluegrass, Poa pratensis L.). In addition, the cell wall monosaccharide and ester-linked hydroxycinnamic acid contents were determined for each grass. The developed method revealed unique structural aspects of the AX structure of these forage grass samples that complemented the results of the cell wall monosaccharide analysis. For example, xylotriose, representing an unsubstituted portion of the AX polysaccharide backbone, was the most abundantly-released oligosaccharide in all the species. Perennial rye samples tended to have greater amounts of released oligosaccharides compared to the other species. This method is ideally suited to monitor structural changes of AX in forages as a result of plant breeding, pasture management, and fermentation of plant material.

In-syringe dispersive solid phase filter extraction cleanup followed by liquid chromatography-triple quadrupole mass spectrometry for fast determination of colchicine in plasma/urine

As an effective treatment for acute gouty arthritis and cardiovascular disease, colchicine is also a toxic alkaloid and may cause poisoning or even death in overdose. The study of colchicine elimination and the diagnosis of poisoning etiology need the rapid and accurate quantitative analysis method in biological matrix. An analytical method was developed for colchicine in plasma and urine by in-syringe dispersive solid phase extraction (DSPE) followed by liquid chromatography-triple quadrupole mass spectrometry (LC-MS/MS). Sample extraction and protein precipitation were proceeded with acetonitrile. The extract was cleaned by in-syringe DSPE. An XBridge™ BEH C18 column（100 mm × 2.1 mm, 2.5 µm）was used to separate colchicine by gradient elution with mobile phase of 0.01% (v/v) ammonia-methanol. The amount and filling sequence of magnesium sulfate (MgSO4) and primary secondary amine (PSA) suitable for in-syringe DSPE were studied. Scopolamine was screened as the quantitative internal standard (IS) for colchicine analysis according to the consistency of recovery rate, chromatographic retention time and matrix effects. The limits of detection for colchicine in plasma and urine were both 0.06 ng mL−1 and the limits of quantitation were both 0.2 ng mL−1. The linear range was 0.04 – 20 ng mL−1 (Equivalent to 0.2–100 ng mL−1 in plasma or urine) with a correlation coefficient r > 0.999. By IS calibration, the average recoveries at three spiking levels in plasma and urine were 95.3–102.68% and 93.9–94.8% with the relative standard deviations (RSDs) of 2.9–5.7% and 2.3–3.4%, respectively. The matrix effects, stability, dilution effects and carryover for determination of colchicine in plasma and urine were also evaluated. The elimination of colchicine within 72–384 h post-ingestion was studied for a poisoning patient with the doses of 1 mg d−1 for 39 days and then 3 mg d−1 for 15 days).

Simple In Vitro 18O Labeling for Improved Mass Spectrometry-Based Drug Metabolites Identification: Deep Drug Metabolism Study.

The identification of drug metabolites formed with different in vitro systems by HPLC-MS is a standard step in preclinical research. In vitro systems allow modeling of real metabolic pathways of a drug candidate. Despite the emergence of various software and databases, identification of compounds is still a complex task. Measurement of the accurate mass, correlation of chromatographic retention times and fragmentation spectra are often insufficient for identification of compounds especially in the absence of reference materials. Metabolites can "slip under the nose", since it is often not possible to reliably confirm that a signal belongs to a metabolite and not to other compounds in complex systems. Isotope labeling has proved to be a tool that aids in small molecule identification. The introduction of heavy isotopes is done with isotope exchange reactions or with complicated synthetic schemes. Here, we present an approach based on the biocatalytic insertion of oxygen-18 isotope under the action of liver microsomes enzymes in the presence of 18O2. Using the local anesthetic bupivacaine as an example, more than 20 previously unknown metabolites were reliably discovered and annotated in the absence of the reference materials. In combination with high-resolution mass spectrometry and modern methods of mass spectrometric metabolism data processing, we demonstrated the ability of the proposed approach to increase the degree of confidence in interpretating metabolism data.

Suitability of skin-PAMPA and chromatographic systems to emulate skin permeation. Influence of pH on skin-PAMPA permeability

The skin permeation, Kp, of a chemical compound is a relevant parameter in fields such as toxicology, exposure to pollutants, or dermal studies of pharmaceutical and cosmetic interest. Nonetheless, its experimental determination is not a trivial task, and for this reason alternative methods to estimate Kp have been developed.This work evaluates the suitability of different methodologies to estimate skin permeation of neutral compounds. Three different approaches have been examined: estimation through the skin-PAMPA (Parallel Artificial Membrane Permeability Assay) permeability, Pe, estimation through the chromatographic retention factor combined with molecular volume, and finally estimation through a quantitative structure–property relationship (QSPR) based on the octanol–water partition coefficient, log Po/w, and molecular volume as descriptors. The three approaches have been tested with the same set of compounds and it has been observed that all of them can be used to estimate Kp with similar results, although the chromatographic method presents slightly improved statistics in addition to the facility of measurement.As many drugs are partially ionised at the pH of skin, the influence of pH in skin-PAMPA permeability has been also studied. To this end, the log Pe vs. pH profiles of a set of 25 compounds of different nature have been determined. As expected, the permeation of neutral forms is higher than the one of ionic forms, and permeation of neutral and ionic species are not governed by the same mechanisms.

Preparation of poly(N-vinylpyrrolidone-co-pentaerythritol triacrylate) monolithic column for hydrophilic interaction chromatography.

A method for the preparation of poly(N-vinylpyrrolidone-co-pentaerythritol triacrylate copolymerization)-based monolithic capillary column was reported for the separation of polar small molecular weight compounds with nano-liquid chromatography in hydrophilic interaction chromatography mode. The monolithic columns were prepared by in situ copolymerization of N-vinylpyrrolidone and a cross-linker pentaerythritol triacrylate in a binary porogenic agent consisting of methanol and water. The composition of the polymerization solution was systematically optimized in terms of column permeability, theoretical plate number, asymmetric factor, and retention factor. A typical hydrophilic chromatography retention mechanism was observed with a mobile phase composed of a high content of organic solvent. The preparation method is simple and robust, the precursor N-vinylpyrrolidone is chemically stable, cheap, and easily available. The N-vinylpyrrolidone-based hydrophilic interaction chromatography stationary phase displays satisfactory separation selectivity for a range of polar test analytes, including benzoic acid derivatives, nucleosides, and phenols.

Polyvalent incorporation of anionic β-cyclodextrin polymers into layer-by-layer coatings

As versatile compounds forming host-guest complexes with a wide variety of hydrophobic molecules, cyclodextrins are widespread candidates to confer functionalities to surfaces, particularly for drug delivery applications in the field of biomaterials, and for analytic or preparative purposes in separative sciences. We report here on Layer-by-Layer coatings used to decorate surfaces with β-cyclodextrins, based on their capacity to allow the stress-free immobilization, and to maintain the accessibility and activity of functional components. We incorporated a β-cyclodextrin polymer into the coatings, either as the polyanionic component in association with polycationic polyethyleneimine or poly-l-lysine, or by post-loading into chondroitin sulfate/poly-l-lysine films. The study of the buildup mechanism, the structural features, and the interactions of the coatings with racemic mixtures of chiral hydrophobic compounds, provided evidence of the effective incorporation of the cyclodextrins and of their preserved functionality. The post-loading protocol led to noticeably high amounts of incorporated cyclodextrin polymer, which made it an unique, efficient route to embed cyclodextrins into Layer-by-Layer architectures. All the cyclodextrin-enriched films improved the chromatographic retention of hydrophobic compounds, and the polyethyleneimine/cyclodextrin systems showed additional enantioseparation properties. We view our coatings as relevant candidates for the design of drug nanoreservoirs atop biomaterials, and stationary phases in chromatographic devices.

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.

Using Thermodynamics and Simulations to Understand Selectivity and Retention in Gas Chromatography

Retention and selectivity in gas chromatography (GC) occur because of the thermodynamics of the phase transition from the vapor phase following sample injection to the solution phase of being dissolved in the stationary phase. Analytes then move along the column because the vapor phase is flowing. In this installment, we quickly review the basic thermodynamics underlying separation in GC, and we see how this impacts selectivity and retention. Last month, we saw how seemingly large differences in column polarity may still generate little, or even the opposite, effect on retention and generate confusion and difficulty in method development. This month, we explore this challenge more in-depth using thermodynamics and a freely available online GC simulator.

Determination of Abraham Model Solute Descriptors for 62 Additional C10 through C13 Methyl- and Ethyl-Branched Alkanes

Abraham model solute descriptors are reported for the first time for 62 additional C10 through C13 methyl- and ethyl-branched alkanes. The numerical values were determined using published gas chromatographic retention Kováts retention indices for 157 alkane solutes eluted from a squalane stationary phase column. The 95 alkane solutes that have known descriptor values were used to construct the Abraham model KRI versus L-solute descriptor correlation needed in our calculations. The calculated solute descriptors can be used in conjunction with previously published Abraham model correlations to predict a wide range of important physico-chemical and biological properties. The predictive computations are illustrated by estimating the air-to-polydimethylsiloxane partition coefficient for each of the 157 alkane solutes.