Quantitative Structure-Retention Relationship Studies with Biopartitioning Micellar Chromatography Systems by Amended Linear Solvation Energy Relationships in Consideration of Electronic Factor

Linear solvation energy relationship (LSER) amended by the introduction of a molecular electronic factor was employed to establish quantitative structure-retention relationship of biopartitioning micellar chromatography (BMC) system. The chromatographic indices, log k, were determined by LC on a C18 column for sixty-five structurally diverse compounds, including neutral (32), acidic (19) and basic (14) compounds. Two micellar mobile phases composed of 0.04 mol L^?1 polyoxyethylene (23) lauryl ether (Brij35) were adjusted by phosphate buffer to pH 7.4 and pH 6.5, respectively. When the mean net charge per molecule (δ) was introduced into LSER as the sixth variable, the LSER regression coefficients and predictive capability were significantly improved. However, the δ coefficients of the amended LSER were quite different for acidic and basic compounds, indicating that the molecular electronic factor had a markedly different impact on the retention of acidic and basic compounds in the studied BMC system. This may attribute to the extra interaction for ionized compounds with the free silanol groups in the stationary phase. The comparison of calculated and experimental retention indices suggested that the amended LSER could reproduce adequately the retention of the structurally diverse solutes investigated in BMC.     

Experimental and computational study of the thermal decomposition of 3-buten-1-ol in m-xylene solution

An experimental study of the thermal decomposition of a β-hydroxy alkene, 3-buten-1-ol, in m-xylene solution, has been carried out at three different temperatures: 553.15, 573.15, and 593.15 K. The temperature dependence of the rate constants for the decomposition of this compound in the corresponding Arrhenius equation is given by ln k (s^?1) = (27.34 ± 1.24)–(19,328 ± 712) (kJ mol^?1) T ^?1. A computational study has been performed at the MP2/6-31+G(d) level of theory to calculate the rate constants and the activation parameters by the classical transition state theory. The Arrhenius equation obtained theoretically, ln k (s^?1) = (28.252 ± 0.025)–(19,738.0 ± 14.4) (kJ mol^?1) T ^?1, agrees very satisfactorily with the experimental one. The bonding characteristics of reactant, transition state, and products have been investigated by the natural bond orbital analysis which provides the natural atomic charges and the Wiberg bond indices used to follow the progress of the reaction. The enthalpy of the reaction has been calculated using experimental values taken from literature and theoretic calculations. The agreement between both values is satisfactory.     

SDS-Based Biomembrane Mimetic Chromatography for Prediction of Human Drug Transport as an in Vitro Technique

The main oral drug absorption barriers are fluid cell membranes, and generally drugs are absorbed by a passive diffusion mechanism. On the other hand, the blood–brain barrier (BBB) is considered to be the main barrier to drug transport into the central nervous system (CNS). The BBB restricts the passive diffusion of many drugs from blood to brain. Biopartitioning micellar chromatography (BMC), a mode of micellar liquid chromatography that uses micellar mobile phases in adequate experimental conditions, can be useful as an in vitro system in mimicking the drug partitioning process into biological systems. In this study, relationships between the BMC retention data of a heterogeneous set of 12 drugs and their pharmacokinetics parameters (human oral drug absorption and BBB penetration ability) are studied and the predictive ability of the models is evaluated. Modeling of log k _BMC of these compounds was established by multiple linear regression in two different concentrations (0.07 and 0.09 M) of sodium dodecyl sulfate (SDS). The results showed a fair correlation between human oral drug absorption and BMC retention data in 0.09 M SDS (R ² = 0.864) and a good correlation between the blood–brain distribution coefficient and BMC retention data in 0.07 M of SDS (R ² = 0.887). Application of the developed models to a prediction set demonstrated that the model is also reliable with good predictive accuracy. The external and internal validation results showed that the predicted values are in good agreement with the experimental value.     

Using high-performance quantitative NMR (HP-qNMR®) for certifying traceable and highly accurate purity values of organic reference materials with uncertainties <0.1 %

Quantitative nuclear magnetic resonance (qNMR) in combination with metrological weighing is optimised to demonstrate the power of the qNMR measurement method. It is shown that with ¹H-qNMR it is possible to certify the purity of organic reference materials (expressed as mass fraction) with relative expanded uncertainties of <0.1 % for a 95 % confidence interval (k = 2). Following well-defined selection criteria, a set of twelve different chemical compounds is evaluated and certified to serve as internal references for ¹H-qNMR measurements. A series of comparison measurements is made amongst a subset of the selected compounds. The purity of maleic acid is determined by six different ¹H-qNMR measurement series, and all results show full consistency. All the six mean values are covered within the range of ±0.05 %. In two more measurement series, four different nuclei are analysed within the same sample against one calibrator. Even with non-optimised signal intensity ratios and varying signal pattern, a high consistency was obtained. Therefore, the validity and robustness of ¹H-qNMR measurement results are demonstrated. ¹H-qNMR measurement results are directly traceable to a variety of internationally accepted primary reference materials, and therefore, traceability to SI units is obtained. All experiments are performed under ISO/IEC 17025 and ISO Guide 34 accreditation.     

Metabolite profiling and beyond: approaches for the rapid processing and annotation of human blood serum mass spectrometry data

In this paper, we describe data processing and metabolite identification approaches which lead to a rapid and semi-automated interpretation of metabolomics experiments. Data from metabolite fingerprinting using LC-ESI-Q-TOF/MS were processed with several open-source software packages, including XCMS and CAMERA to detect features and group features into compound spectra. Next, we describe the automatic scheduling of tandem mass spectrometry (MS) acquisitions to acquire a large number of MS/MS spectra, and the subsequent processing and computer-assisted annotation towards identification using the R packages MetShot, Rdisop, and the MetFusion application. We also implement a simple retention time prediction model using predicted lipophilicity logD, which predicts retention times within 42 s (6 min gradient) for most compounds in our setup. We putatively identified 44 common metabolites including several amino acids and phospholipids at metabolomics standards initiative (MSI) levels two and three and confirmed the majority of them by comparison with authentic standards at MSI level one. To aid both data integration within and data sharing between laboratories, we integrated data from two labs and mapped retention times between the chromatographic systems. Despite the different MS instrumentation and different chromatographic gradient programs, the mapped retention times agree within 26 s (20 min gradient) for 90 % of the mapped features.

Autoignition temperature: comprehensive data analysis and predictive models

ABSTRACT

Here we report a new predictive model for autoignition temperature (AIT), an important physical parameter widely used to assess potential safety hazards of combustible materials. Available structure-AIT data extracted from different sources were critically analysed. Support vector regression (SVR) models on different data subsets were built in order to identify a reliable compound set on which a realistic model could be built. This led to a selection of the dataset containing 875 compounds annotated with AIT values. The thereupon-based SVR model performs reasonably well in cross-validation with the determination coefficient r ² = 0.77 and mean absolute error MAE = 37.8°C. External validation on 20 industrial compounds missing in the training set confirmed its good predictive power (MAE = 28.7°C).     

Kinetic and thermodynamic parameters of volatilization of biodiesel from babassu, palm oil and mineral diesel by thermogravimetric analysis (TG)

The boiling point and volatility are important properties for fuels, as it is for quality control of the industry of petroleum diesel and biofuels. In addition, through the volatility is possible to predict properties, such as vapor pressure, density, latent heat, heat of vaporization, viscosity, and surface tension of biodiesel. From thermogravimetry analysis it is possible to find the kinetic parameters (activation energy, pre-exponential factor, and reaction order), of thermally simulated processes, like volatilization. With the kinetic parameters, it is possible to obtain the thermodynamic parameters by mathematical formula. For the kinetic parameters, the minor values of activation energy were found for mineral diesel (E = 49.38 kJ mol^?1), followed by babassu biodiesel (E = 76.37 kJ mol^?1), and palm biodiesel (E = 87.00 kJ mol^?1). Between the two biofuels studied, the babassu biodiesel has the higher minor value of activation energy. The thermodynamics parameters of babassu biodiesel are, ΔS = ?129.12 J mol^?1 K^?1, ΔH = +80.38 kJ mol^?1 and ΔG = +142.74 kJ mol^?1. For palm biodiesel ΔS = ?119.26 J mol^?1 K^?1, ΔH = + 90.53 kJ mol^?1 and ΔG = +141.21 kJ mol^?1, and for diesel ΔS = ?131.3 J mol^?1 K^?1, ΔH = +53.29 kJ mol^?1 and ΔG = +115.13 kJ mol^?1. The kinetic thermal analysis shows that all E, ΔH, and ΔG values are positive and ΔS values are negative, consequently, all thermodynamic parameters indicate non-spontaneous processes of volatilization for all the fuels studied.     

A new version of an additive scheme for the prediction of gas chromatographic retention indices of the 211 structural isomers of 4-nonylphenol

Control of environmental pollution by 4-nonylphenols (4-NP) and effective risk assessment concerning these xenoestrogens requires the identification of the individual isomers contained in the technical mixtures of 4-NP. A new approach is presented here which supports the identification of these compounds by a combination of experimentally determined gas chromatographic retention indices (I) of reference 4-NP isomers and calculated I-values. In addition to experimental indices, the I-prediction algorithm includes a new version of an additive scheme. The I-values of all structural 4-NP isomers are calculated on the basis of experimentally determined indices of a few available 4-NP isomers and the known retention indices of 75 iso-decanes. A mean deviation of ±11 index units between predicted and experimental I-values demonstrates the feasibility of the new approach. The predicted I-values provide information on the structure of 4-nonylphenol isomers in the technical mixture which has not been considered before. Furthermore, a novel line-coding system is proposed to describe the structure of isomeric 4-NPs and to initiate a current database for the endocrine-disrupting 4-nonylphenols.     

Preparation of an ionic liquid-mediated carbon nanotube-poly(dimethylsiloxane) fiber by sol–gel technique for determination of polycyclic aromatic hydrocarbons in urine samples using head-space solid-phase microextraction coupled with gas chromatography

A novel ‘ionic liquid-mediated multi-walled carbon nanotube (MWCNT)-poly(dimethylsiloxane) (PDMS)’ hybrid coating was prepared by the covalent functionalization of MWCNTs with hydroxyl-terminated PDMS using the sol–gel technique. The prepared fiber was successfully used for the separation and determination of trace amounts of polycyclic aromatic hydrocarbon compounds (PAHs) in four urine samples using head-space solid-phase microextraction coupled to gas chromatography-flame ionization detection. The proposed fiber has high thermal stability and long durability and it can be used more than 210 times without any significant change in its sorption properties. The effects of important parameters such as the exposure time, sampling temperature, sample ionic strength and stirring rate on the extraction efficiency have been studied and optimized. Under the optimal conditions, the method detection limits (S/N = 3) were in the range of 0.0005–0.004 ng mL^?1 and the limits of quantification (S/N = 10) between 0.002 and 0.01 ng mL^?1. The relative standard deviations for one fiber (repeatability, n = 5) were 4.9–7.5 % and for the fibers obtained from different batches (reproducibility, n = 3), 6.1–8.9 %. The developed method was successfully applied to determine trace levels of PAHs in real urine samples. The obtained relative recoveries for the spiked samples with 0.05 ng mL^?1 of each of the PAH compounds were 89.3–107.2 %.     

Preparation and performance valuation of high selective molecularly imprinted polymers for malachite green

Molecular imprinting is a technology that facilitates the production of artificial receptors toward compounds of interest. In this study, we prepared a series of molecularly imprinted polymers (MIPs) by precipitation polymerization for the purpose of binding specifically to malachite green (MG). The presence of monomer–template solution complexes in non-covalent MIPs systems had been verified by UV-spectrometric detection and molecular dynamics simulations. The synthesized parameters were, respectively, optimized and the optimal conditions for the efficient adsorption property were as follows: template: MG, 1 mmol; functional monomer: methacrylic acid (MAA), 8 mmol; cross-linker: ethylene glycol dimethacryllate, 16 mmol; and porogen: acetonitrile, 30 mL. Fourier transform infrared spectroscopy and nitrogen adsorption experiments were used to characterize the MIPs. Scatchard analysis was used for estimation of the dissociation constants and maximum amounts of binding sites. The polymer based on MAA had two classes of heterogeneous binding sites characterized by two values of K _D and B _max: K _D = 14.10 μmol L^?1 and B _max = 1.37 μmol g^?1 for the higher affinity binding sites, and K _D = 384.62 μmol L^?1 and B _max = 24.77 μmol g^?1 for the lower affinity binding sites. The specificity of MIPs on SPE column was evaluated by rebinding the other structurally similar compounds. The results indicated that the imprinted polymers exhibited an excellent stereo-selectivity toward MG.     

Monte Carlo-based QSAR modeling of dimeric pyridinium compounds and drug design of new potent acetylcholine esterase inhibitors for potential therapy of <Emphasis Type="Italic">myasthenia gravis</Emphasis>

The Monte Carlo method was used for QSAR modeling of dimeric pyridinium compounds as acetylcholine esterase inhibitors. QSAR model was developed for a series of 39 dimeric pyridinium compounds. QSAR models were calculated with the representation of the molecular structure by the simplified molecular-input line-entry system. One split into the training and test set have been examined. The statistical quality of the developed model is very good. The calculated model for dimeric pyridinium derivatives had following statistical parameters: r ² = 0.9477 for the training set and r ² = 0.9332 the test set. Structural indicators considered as molecular fragments responsible for the increase and decrease in the inhibition activity have been defined. The computer-aided design of new dimeric pyridinium compounds potential acetylcholine esterase inhibitors with the application of defined structural alerts has been presented.     

Rapid Estimation of Octanol–Water Partition Coefficient for Triazole Fungicides by MEKC with Sodium Deoxycholate as Surfactant

A rapid estimation of octanol–water partition coefficient (log P _ow) was developed for triazole fungicides by micellar electrokinetic chromatography (MEKC). Five standard compounds with known log P _ow values from 2.9 to 4.3 (cyproconazole, bromuconazole, epoxiconazole, bitertanol and difenoconazole) were used for constructing the calibration curve of the log P _ow against the MEKC retention factor, log k. A linear relationship was achieved between log P _ow and log k, in the MEKC system containing 40 mM sodium deoxycholate (SDC) and 4 mM borate buffer at pH 9.3, with a correlation of determination, r ² = 0.9905. The log P _ow values of four test compounds of triazole fungicides (triadimenol, myclobutanil, propiconazole and penconazole) were calculated based on the log k values measured by MEKC and the slope and intercept of the calibration curve. This MEKC method can give good estimation of the log P _ow of the four test compounds of triazole fungicides with the differences between the literature log P _ow values and estimated log P _ow from the MEKC method were from 0.15 to 0.23 log units.