Comparative multiple quantitative structure–retention relationships modeling of gas chromatographic retention time of essential oils using multiple linear regression, principal component regression, and partial least squares techniques

Comprehensive binding analysis of polybrominated diphenyl ethers and aryl hydrocarbon receptor via an integrated molecular modeling approach

Polybrominated diphenyl ethers (PBDEs) are often suspected to activate the signal transduction pathway of aryl hydrocarbon receptor (AhR), a ligand-activated transcription factor, for the induction of toxicity. Hence, the binding property of PBDEs with AhR is assumed to be associated with the ligand-dependent activation of AhR that may introduce many drug-metabolizing enzymes of genes encoding. However, the binding mechanism and the structural effect of PBDEs on their binding properties of AhR still need to be unraveled for toxicology research. A comprehensive study of the PBDEs-AhR binding mechanism was investigated using an integrated molecular modeling approach with two-dimensional quantitative structure-activity relationships (2D-QSAR), three-dimensional QSAR (3D-QSAR), and molecular docking simulation. Molecular docking revealed the differences in binding domains among 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-AhR complex and two PBDE-AhR complexes. A 2D-QSAR model was developed to analyze the overall structural effects of PBDEs on the binding affinity of AhR. It provided an insight into major physico-chemical properties by multiple linear regression based on genetic algorithm with reasonable results. The 3D-QSAR modeling discovered the detailed interaction features of binding sites, configurations and interaction fields of AhR with different PBDE ligands. This study demonstrated that the descriptors of Smin69 and MoRSEC15 were related to electronic properties and had a great effect on the relative binding affinities. The position of Br substitutions exhibited a significant influence on the interactions between AhR and PBDEs, including halogen interaction, π-S interaction, π-π stacking interaction, and hydrophobic effect. This integrated molecular modeling approach provided a comprehensive analysis of the structural effects of PBDEs on their binding properties with AhR at molecular level.

A fast and selective gas liquid microextraction of semiochemicals for quantitative analysis in plants

A trapping-based gas liquid microextraction (GLME) method coupled with gas chromatography-mass spectrometry (GC-MS) was utilized to qualitatively and quantitatively characterize semiochemicals in plants. The main GLME extraction efficiency associated parameters (heating temperature and extraction time) were optimized. The results obtained from GLME process were compared with those of steam distillation and ultrasonic extraction, and the recovery, peak number and reproducibility were evaluated by using Thuja koraiensis Nakai as a representative plant. Furthermore, the quantitative performances of the GLME in terms of sample amount, recoveries of spiked standards and correlation were systematically evaluated using standard addition method, which gave a good quantitative ability for all the compounds with squares of correlation coefficient (r²) of higher than 0.99. Finally, the contents of α-pinene, camphene, linalool, α-terpinenol, β-caryophyllene, α-caryophyllene, and totarol in Thuja koraiensis Nakai samples were quantified, and their concentrations (SD, n = 3) were; 0.65 (0.06), 0.62 (0.05), 4.12 (0.15), 0.99 (0.08), 1.11 (0.07), 0.63 (0.04), and 21.91 (0.25) μg g^-1, respectively. It was demonstrated that GLME is a powerful sample preparation technique for quantitative and qualitative analysis of plant semiochemicals.

Atom-Type-Based AI Topological Indices for Artificial Neural Network Modeling of Retention Indices of Monomethylalkanes

In this work, a combination of Xu and atom-type-based AI topological indices (TIs) were employed for quantitative structure-retention relationship (QSRR) study of monomethylalkanes (MMAs). A total of 196 temperature-programmed gas chromatographic retention indices corresponding to all C4-C30 MMAs on OV-1 stationary phase have been used in QSRR modeling. Results of the study showed that an artificial neural network (ANN) with 4-9-1 topology and Levenberg-Marquardt training algorithm can predict the retention indices with high degree of accuracy. The statistics of root-mean-square error for the training, validation and test sets were 0.200, 0.316 and 0.215, respectively. The proposed model resulted in a maximum relative error of 0.24% suggesting the TIs as excellent alternative for estimating retention indices of MMAs. According to the obtained results, relative importance of the TIs decreased in the order of AI(-CH3)> AI(-CH2-)> AI(>CH-)> Xu showing significant role of molecular branching, steric factor and molecular size as effective structural features on retention indices of MMAs.

A review of the preparation and application of flavour and essential oils microcapsules based on complex coacervation technology

This paper briefly introduces the preparation and application of flavour and essential oils microcapsules based on complex coacervation technology. The conventional encapsulating agents of oppositely charged proteins and polysaccharides that are used for microencapsulation of flavours and essential oils are reviewed along with the recent advances in complex coacervation methods. Proteins extracted from animal-derived products (gelatin, whey proteins, silk fibroin) and from vegetables (soy proteins, pea proteins), and polysaccharides such as gum Arabic, pectin, chitosan, agar, alginate, carrageenan and sodium carboxymethyl cellulose are described in depth. In recent decades, flavour and essential oils microcapsules have found numerous potential practical applications in food, textiles, agriculturals and pharmaceuticals. In this paper, the different coating materials and their application are discussed in detail. Consequently, the information obtained allows criteria to be established for selecting a method for the preparation of microcapsules according to their advantages, limitations and behaviours as carriers of flavours and essential oils.